Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@products-mcp-server recommend products similar to id 5"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A custom Model Context Protocol (MCP) server exposing 27 product tools backed by fakestoreapi.com.
It runs three ways from the same code:
Local (stdio) — for Cursor / Claude Desktop, via src/index.ts → dist/index.js.
Render (persistent HTTP) — a long-running Streamable HTTP server, via src/http.ts → dist/http.js.
Vercel (serverless HTTP) — a stateless Streamable HTTP function, via api/mcp.ts.
src/
products-api.ts # Fake Store API client (endpoints + 60s TTL cache)
tools.ts # registerTools(server): all 27 tools (shared)
server.ts # createServer(): builds a configured server (shared)
index.ts # stdio entry point (local)
http.ts # persistent HTTP entry point (Render) — listens on $PORT
api/
mcp.ts # Vercel serverless entry point (stateless Streamable HTTP)
render.yaml # Render blueprint (web service)
vercel.json # Vercel function configAll entry points call createServer(), so the tool set stays identical across transports.
Related MCP server: MCP E-commerce Server
# | Tool | Description |
1 |
| All products (optional |
2 |
| One product by |
3 |
| List of categories. |
4 |
| Products in a |
5 |
| Keyword search over title + description. |
6 |
| Products within |
7 |
| Products costing more than |
8 |
| Products costing less than |
9 |
| Single cheapest product. |
10 |
| Single most expensive product. |
11 |
| Sorted by rating (optional |
12 |
| Sorted by review count (optional |
13 |
| Products with rating >= |
14 |
| count / min / max / average / median / total. |
15 |
| Per-category price stats. |
16 |
| Total count (optional |
17 |
| Lightweight id + title list. |
18 |
| A random product. |
19 |
| Compare 2–10 products by |
20 |
| Same-category picks for an |
21 |
| Price after |
22 |
| High-level catalog summary. |
23 |
| Cheapest within a |
24 |
| Highest-rated within a |
25 |
| Create a product (simulated by the API). |
26 |
| Update a product (simulated). |
27 |
| Delete a product (simulated). |
Note: fakestoreapi.com simulates write operations (create/update/delete) and does not persist them.
npm install
npm run build # tsc: src -> dist
npm run typecheck # type-checks src + api
npm start # runs the stdio server~/.cursor/mcp.json){
"mcpServers": {
"products": {
"command": "node",
"args": ["c:/Users/serch/OneDrive/Desktop/MCP-Servers/products-mcp-server/dist/index.js"]
}
}
}Re-run npm run build after changing the TypeScript, since Cursor runs the compiled dist/index.js.
To run the HTTP server locally (same one Render uses):
npm run build
npm run start:http # listens on http://localhost:3000/mcp
# health check: curl http://localhost:3000/healthzRender runs a persistent Node process (via src/http.ts), which suits MCP well and avoids serverless cold starts / timeouts.
The repo includes render.yaml:
services:
- type: web
name: products-mcp-server
runtime: node
plan: free
buildCommand: npm install && npm run build
startCommand: npm run start:http
healthCheckPath: /healthzPush this folder to a Git repo.
In Render: New → Blueprint, select the repo. Render reads render.yaml and creates the web service.
Deploy. Your endpoint will be:
https://<your-service>.onrender.com/mcpNew → Web Service → connect the repo, then set:
Runtime: Node
Build Command: npm install && npm run build
Start Command: npm run start:http
Health Check Path: /healthz
{
"mcpServers": {
"products": { "url": "https://<your-service>.onrender.com/mcp" }
}
}For stdio-only clients, bridge with mcp-remote:
{
"mcpServers": {
"products": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://<your-service>.onrender.com/mcp"]
}
}
}The server binds to process.env.PORT (Render sets this automatically). The MCP path defaults to /mcp and can be overridden with the MCP_PATH env var.
Render's free web services sleep after inactivity; the first request after idle may be slow to wake.
The deployed URL is public — add authentication before exposing sensitive tools.
The api/mcp.ts function serves the MCP server over Streamable HTTP in stateless mode (a fresh server per request — no Redis required).
Push this folder to a Git repo and import it in Vercel (or run npx vercel).
Vercel compiles api/mcp.ts automatically; no build step is required for the function.
After deploy, your endpoint is:
https://<your-project>.vercel.app/api/mcpIf the client supports Streamable HTTP (e.g. recent Cursor):
{
"mcpServers": {
"products": { "url": "https://<your-project>.vercel.app/api/mcp" }
}
}For stdio-only clients, bridge with mcp-remote:
{
"mcpServers": {
"products": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://<your-project>.vercel.app/api/mcp"]
}
}
}Stateless: each request is self-contained. If you later need SSE streaming / persistent sessions across instances, add Upstash Redis and enable Vercel Fluid Compute.
Timeout: vercel.json sets maxDuration: 60; each tool also has a 10s upstream-fetch abort guard.
Auth: the deployed URL is public. Add authentication before exposing sensitive tools.
Compares two or more products side by side by their ids.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It lacks details on what the comparison entails (e.g., output format, side-by-side display, or any side effects). It only mentions input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the key action and resource, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter, lack of output schema, and no annotations, the description is minimally adequate but does not explain the output format, behavior, or error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal meaning to the 'ids' parameter beyond the schema, stating 'by their ids'. With 0% schema description coverage, it provides some context but does not explain format or constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares two or more products by their IDs, with a specific verb and resource. However, it does not distinguish from siblings like 'getProducts' or 'getProductById' beyond the comparative aspect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied: use when comparing products. No explicit guidance on when not to use or alternatives among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Counts products, optionally filtered by category.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It implies a read-only operation but does not explicitly confirm non-destructive behavior or any limits (e.g., count maxima).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise, but could be slightly more informative without sacrificing brevity (e.g., specifying output type).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is minimal but sufficient for a simple count operation. Lacks details on return format or error cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description only adds 'optionally filtered by category' without explaining valid category values or format. The parameter's semantics remain vague.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool counts products with optional category filtering, distinguishing it from siblings like getProducts (returns list) and getCategoryStats (returns statistics).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as getProducts (for retrieving product data) or getCategories (for listing categories).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Creates a product. Note: fakestoreapi.com simulates writes and does not persist them.
| Name | Required | Description | Default |
|---|---|---|---|
| image | Yes | ||
| price | Yes | ||
| title | Yes | ||
| category | Yes | ||
| description | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description includes an important note that writes are simulated and not persisted, which adds behavioral context beyond the absence of annotations. However, it lacks details on return values, error handling, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence plus a note) but lacks essential parameter information, making it inefficient for agent use despite being concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with 5 required parameters and no output schema, the description omits critical details such as the return value, expected behavior on success/failure, and any constraints on parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the 5 parameters (image, price, title, category, description). The agent only has parameter names and types from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Creates a product' which is a specific verb+resource. It distinguishes from sibling tools like updateProduct and deleteProduct, though it could be more precise about the product creation context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like updateProduct or getProducts. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Deletes a product by id. Note: fakestoreapi.com simulates writes and does not persist them.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the API simulates writes and does not persist, which is critical behavioral info. However, it omits details on idempotency, error handling (e.g., nonexistent id), and return value, leaving gaps for agents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. Front-loaded with the action verb. Efficiently communicates core purpose and key caveat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required param, no output schema), the description covers purpose and the simulation note. However, it lacks information on return behavior (e.g., does it return the deleted product or a status code?) and error conditions, which would help agents handle responses correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It mentions 'by id' but provides no further semantics about the id parameter (e.g., format, validation, or expected value). The description adds minimal value beyond the schema's type and required constraint.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Deletes' and the resource 'product by id', making the tool's action unambiguous. It distinguishes from sibling tools like updateProduct and createProduct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives, but the purpose is straightforward and the limitation (simulation) is noted. Minimal guidance is acceptable for a simple delete operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the list of available product categories.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description only states it returns a list, with no mention of side effects, authentication, or rate limits. For a simple read tool this is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is appropriately sized and front-loaded for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (0 parameters, no output schema), the description is minimally complete. However, it could add context about the output format (e.g., list of names/IDs) to fully inform the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the description does not need to add meaning beyond the schema. The baseline for 0 parameters is 4, and the description meets expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and resource ('list of available product categories'), clearly indicating the tool's function. It distinguishes from siblings that deal with products, but does not specify the format or structure of the categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus siblings. No context, prerequisites, or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns per-category product count and average/min/max price.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns aggregated statistics per category, which is sufficient for a simple read operation. However, it could mention that it aggregates across all products or any potential performance implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the essential functionality without any filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately states what is returned (product count and average/min/max price per category). It could be slightly more complete by specifying the output format, but for a simple aggregation tool, it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and the schema has 100% coverage trivially. Baseline is 4 for zero-parameter tools. The description does not need to add parameter information, and it correctly omits any.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Returns' and identifies the resource 'per-category product count and average/min/max price'. It clearly distinguishes from siblings like getPriceStats (overall stats) and getCheapestInCategory (specific product).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as getPriceStats or getCategories. The usage is only implied by the description, with no when-not-to-use or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the cheapest product within a given category.
| Name | Required | Description | Default |
|---|---|---|---|
| category | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits beyond the basic operation. It fails to explain behavior for missing categories, ties, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short, which is acceptable for a simple tool, but it lacks structure and could be slightly more informative without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one parameter, no output schema, no annotations), the description provides basic level of completeness. However, it does not address return format or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'category' is only described as 'within a given category', adding no meaning beyond the schema's type and minLength constraints. With 0% schema description coverage, the description should compensate but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the cheapest product within a given category, using a specific verb and resource. It is distinct from siblings like 'getCheapestProduct' (likely global) and 'getHighestRatedInCategory'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like 'getCheapestProduct' or 'getProductsByCategory'. Usage is implied but lacks exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the single cheapest product in the catalog.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It does not explain what 'cheapest' means (e.g., base price vs. discounted price), what happens if the catalog is empty, or whether the result is sorted. This is insufficient for a tool with no safety annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no extraneous words. Every word is necessary and earns its place. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and zero parameters, the description is too brief. It does not cover return value format, edge cases (empty catalog), or pricing logic. A more complete description would specify sorting criteria and behavior in exceptional cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and schema coverage is 100%. Per guidelines, the baseline is 4. The description does not add unnecessary parameter info but could clarify the meaning of 'cheapest'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and clearly identifies the resource ('single cheapest product in the catalog'). It distinguishes this tool from siblings like getCheapestInCategory or getMostExpensiveProduct by noting it returns the overall cheapest product.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., getCheapestInCategory). There is no mention of exclusions or context, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Calculates a product's price after applying a discount percentage (0-100).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| discountPercent | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states the calculation behavior but does not disclose whether the product must exist, if errors occur for invalid IDs, or whether it is read-only (likely).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no fluff, front-loaded with the action and resource. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No annotations, no output schema, and only two parameters. The description does not explain return format, prerequisites (product existence), or error conditions, leaving significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains discountPercent range (0-100) but does not describe the id parameter (e.g., product ID). Missing information for half the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculates' and the resource 'product's price after applying a discount percentage', which distinguishes it from sibling tools that retrieve or list products.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like getPriceStats or getProducts. The description does not specify context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the highest-rated product within a given category.
| Name | Required | Description | Default |
|---|---|---|---|
| category | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states the outcome on success but omits edge cases like empty category, tie-breaking, or error handling. Minimal transparency beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately conveys the tool's purpose. No unnecessary words, perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the basic functionality. However, it lacks details on return value structure, edge cases, and potential errors, making it marginally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. While it implies the 'category' parameter is the category name, it does not specify format, valid values, or behavior for invalid input. However, with only one parameter, the implicit meaning is adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the highest-rated product within a given category. It uses a specific verb ('Returns') and resource ('highest-rated product'), and the scope is well-defined. This distinguishes it from sibling tools like getTopRatedProducts (multiple) and getCheapestInCategory.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., getTopRatedProducts, getProductById), the description does not help the agent decide when to choose this one or mention any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the single most expensive product in the catalog.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the return but does not disclose how ties are handled, nor does it confirm whether the entire catalog is considered or if it returns null when empty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words, efficiently conveying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and a simple retrieval, the description lacks details about the return format, what fields the product object contains, and edge cases like an empty catalog.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so baseline is 4 per rules. The description does not need to add parameter info, and schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Returns the single most expensive product in the catalog' uses a specific verb and resource, clearly stating the function. It distinguishes from siblings like getCheapestProduct and getProductsAbovePrice by specifying 'single most expensive'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when the single highest-priced product is needed, but it does not explicitly mention when not to use it or suggest alternatives like getProductsByPriceRange or getPriceStats for more flexibility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns products sorted by number of ratings (highest first).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must convey behavior. It states sorting by rating count but doesn't mention whether products with zero ratings are included, or behavior of the limit parameter. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, no filler. But missing parameter documentation, which is more important than conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with one optional param, yet description omits param explanation and usage context. Incomplete for effective agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'limit' is not mentioned in the description. Schema description coverage is 0%, so description should explain the parameter meaning and constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it returns products sorted by number of ratings (highest first). Distinguishable from siblings like getTopRatedProducts which likely sorts by average rating.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this vs alternatives like getTopRatedProducts or getProducts. With 26 sibling tools, explicit usage context is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns count, min, max, average, median, and total price across all products.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It accurately describes the output statistics but does not mention behavioral traits such as data freshness, performance, or error handling. As a simple read operation, this is adequate but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise, front-loaded with the verb 'Returns', and contains no extraneous information. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity and lack of output schema, the description adequately lists the six statistics it returns. It clarifies the scope as 'across all products'. Minor improvement: could explicitly state that no filtering is supported.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so the schema coverage is 100%. Per guidelines, a baseline of 4 applies. The description adds meaning by specifying what the output contains, which the schema does not address.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states that the tool returns count, min, max, average, median, and total price across all products. It clearly identifies the resource (price stats) and the verb (returns), distinguishing it from sibling tools like getProducts or getCategoryStats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools offering specific price queries (e.g., getCheapestProduct, getMostExpensiveProduct), the tool would benefit from stating that it provides aggregate statistics rather than individual product data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetches a single product by its numeric id.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the basic action without disclosing error behavior (e.g., not found), authentication requirements, rate limits, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, direct sentence with no redundant words. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description is minimally adequate. However, given the lack of output schema and annotations, it does not fully inform the agent about possible return values or error states.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no meaning beyond the schema itself: 'numeric id' simply restates the integer type. No details on format, range, or purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetches') and resource ('single product') with a clear identifier ('numeric id'). It distinguishes from sibling tools like getProducts (list) and searchProducts (by criteria).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as searchProducts or getProducts. No mention of prerequisites (e.g., having the ID) or context for exclusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recommends products in the same category as the given product id.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits like ordering, scoring, or limitations. It only says 'recommends' without explaining the recommendation logic (e.g., random, popular, or all products in the category). This lack of transparency could mislead agents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, very concise, with no wasted words. However, it sacrifices clarity and completeness for brevity, making it insufficiently informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 parameters, no output schema, many siblings), the description is overly minimal. It does not specify the output format, ordering, or how recommendations are generated, leaving significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning to parameters. It does not mention the 'id' parameter (the product ID to base recommendations on) or the 'limit' parameter (max number of recommendations), leaving the agent to infer from the schema's constraints alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it recommends products based on the same category as a given product ID. The verb 'recommends' and resource 'products' are specific, and while it doesn't fully differentiate from siblings like getProductsByCategory, the purpose is generally clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing product recommendations from a product's category, but it provides no explicit guidance on when to use this tool versus alternatives (e.g., getProductsByCategory, getTopRatedProducts). No when-not-to-use or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetches the product catalog from fakestoreapi.com. Optionally limit and sort by id.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | ||
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It mentions optional limit and sort but fails to explain default behavior (e.g., returns all products if no limit), pagination, or any side effects. The description adds limited context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that delivers the core purpose immediately. It is appropriately sized with no extraneous words, earning every word's place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and the tool's role as a general catalog fetcher among 27 siblings, the description is incomplete. It lacks details on default behavior, output format, and when to choose this over more specific tools. More context is needed for an agent to use it reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It adds that the sort parameter sorts 'by id', which is not in the schema, and mentions 'limit'. However, it does not explain the limit meaning (number of products) or default values, which weakens the contribution.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches the product catalog from fakestoreapi.com, with optional limit and sort. It uses a specific verb 'Fetches' and resource 'product catalog', making the purpose clear. However, it does not explicitly differentiate from sibling tools like getProductsByCategory or searchProducts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance on when to use this tool versus siblings. It does not mention scenarios where alternatives like getProductById or getProductsByCategory would be more appropriate. No when-not-to-use or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns products that cost strictly more than the given price.
| Name | Required | Description | Default |
|---|---|---|---|
| price | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses the core filtering logic ('strictly more') but omits details like sorting, pagination, result limits, or error handling. This is minimal but acceptable for a simple filter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no wasted words. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema. The description covers the main purpose but does not mention return format, pagination, or what happens with an empty result. Slightly incomplete but functional.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It clarifies that the comparison is 'strictly more' (exclusive), which adds value beyond the schema's type and minimum. However, it does not specify units, currency, or format, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('returns products') and the condition ('strictly more than the given price'). It is specific and distinguishes this tool from siblings like getProductsBelowPrice and getProductsByPriceRange.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention related tools like getProductsBelowPrice or getProductsByPriceRange, leaving the agent to infer from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns products that cost strictly less than the given price.
| Name | Required | Description | Default |
|---|---|---|---|
| price | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description lacks behavioral details like read-only nature, pagination, sorting, or result limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words, efficiently communicates core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter filter tool, description is largely complete; lacks error handling or result size info but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage; description adds 'strictly less than' clarifying the comparison operator, compensating for schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns products with cost strictly less than given price. Distinct from sibling tools like getProductsAbovePrice and getProductsByPriceRange.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs alternatives. Missing context such as not for price range queries or equality checks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns products in a category (e.g. 'electronics', 'jewelery', "men's clothing", "women's clothing").
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| category | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It only states the basic function, without disclosing any behavioral traits like pagination, ordering, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a single sentence, but could be more structured with separate sentences for parameters and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and two parameters with no descriptions, the description provides insufficient completeness. It lacks details on return format, pagination, or parameter constraints beyond the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description partially compensates by explaining the 'category' parameter with examples, but entirely omits the 'limit' parameter, leaving its purpose unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns products in a category, with illustrative examples. It distinguishes from siblings by specifying category filtering, but does not explicitly differentiate from other filtering tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. The description implies usage for category-based filtering, but lacks when-not scenarios or references to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns products with an average rating >= minRating (0-5).
| Name | Required | Description | Default |
|---|---|---|---|
| minRating | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the basic filtering behavior. It does not disclose whether results are sorted, paginated, or any other behavioral traits such as caching or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words. However, it could be slightly more informative without adding fluff, such as mentioning typical use cases.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter and no output schema, the description is minimal. It lacks details about return format, sorting, limits, or performance characteristics. It is adequate for a simple filter but incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description minimally adds meaning by explaining minRating as 'average rating' and the range. However, it does not elaborate on what 'average rating' means or if it's computed across all reviews, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns products with average rating >= minRating, and specifies the range (0-5). It distinguishes from siblings like getTopRatedProducts and getHighestRatedInCategory by focusing on minimum rating threshold.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool over alternatives like getTopRatedProducts, getHighestRatedInCategory, or getProductsByPriceRange. The user is left to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns products whose price falls within [min, max].
| Name | Required | Description | Default |
|---|---|---|---|
| max | No | ||
| min | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It discloses no behavioral traits beyond the filtering operation: no mention of pagination, ordering, limits, or error handling. The lack of detail reduces transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it sacrifices necessary detail. It is appropriately sized for a simple operation but under-specified for practical use.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is severely incomplete. A two-parameter filter tool needs at least mention of return format, constraint details, or edge cases. The current description leaves critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description adds no meaning beyond the schema. It does not clarify whether min/max are inclusive, required, or how invalid ranges are handled. The description fails to compensate for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns products filtered by price range. The verb 'Returns' and resource 'products' are specific, and the name matches. However, it does not differentiate from siblings like getProductsAbovePrice or getProductsBelowPrice, which limits clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as getProductsAbovePrice or getProductsBelowPrice. The description provides no context for selection, leaving the agent to infer from names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns a single random product from the catalog.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden, but it only states the function without disclosing any behavioral traits like idempotency, side effects, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the essential information with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description adequately describes the tool's purpose. However, it could mention typical use cases like sampling, but overall it is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters (100% coverage), so the description does not need to add parameter information. The baseline is 4, and the description is adequate for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool returns a single random product from the catalog, which is a specific verb+resource combination that distinguishes it from siblings like getProductById or getProducts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as getProducts or getProductRecommendations. The description lacks context for the agent to decide appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns products sorted by rating (highest first).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states that products are sorted by rating but does not explain behavior regarding the 'limit' parameter, default ordering, or handling of ties or empty results. Key behavioral traits are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence), but it omits critical information such as the existence of the 'limit' parameter. While it earns its place for stating purpose, it sacrifices necessary detail, making it merely adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional param, no output schema, no annotations), the description is incomplete. It does not mention the 'limit' parameter or default behavior, and among many sibling tools, it fails to provide sufficient context for correct selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one optional parameter 'limit' with constraints (0-100), but the description provides no explanation of this parameter. Since schema description coverage is 0%, the description must compensate but fails entirely to add meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'returns', the resource 'products', and the sorting criterion 'by rating (highest first)'. It effectively distinguishes this tool from siblings like 'getHighestRatedInCategory' which adds category context, and 'getMostReviewedProducts' which sorts by review count.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidelines are provided about when to use this tool versus the 27 sibling tools. There is no mention of prerequisites, alternatives, or exclusions, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns a lightweight list of product ids and titles.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. 'Lightweight' hints at limited data, but lacks disclosure on pagination, ordering, or response size limits. Behavioral traits are minimally described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise. Every word serves purpose. Could include additional context without being verbose, but current structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema, description gives minimal context. Missing details on whether list is all products or filtered, ordering, or any limitations. Adequate but incomplete given sibling comparison.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, and schema coverage is 100% (vacuous). Description adds no further param info, but baseline for zero parameters is 4. No contradiction.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Returns' and resource 'product ids and titles'. The descriptor 'lightweight' distinguishes it from sibling tools like 'getProducts' which likely return full product objects. Intention is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'getProducts' or 'searchProducts'. Does not specify scenarios where the lightweight result is preferred over full data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Case-insensitive search across product titles and descriptions.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It mentions case-insensitivity but omits details about pagination, sorting, result format, or limits. This is insufficient for an agent to understand side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it sacrifices completeness; a slightly longer description could include more context without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and a simple search tool, the description is incomplete. It fails to clarify what is returned (full products, summaries?), ordering, or handling of multiple results. Sibling tools indicate a rich ecosystem, making this under-specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It explains that 'query' searches across titles and descriptions but does not describe the 'limit' parameter at all. The description adds only partial value for one parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('search') and resource ('products'), and specifies it is case-insensitive across titles and descriptions. However, it does not differentiate from sibling tools like getProducts which may also perform searching, lacking explicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are many sibling tools (e.g., getProductsByCategory, getTopRatedProducts) but no mention of context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns a high-level summary of the catalog: totals, categories, price range, average rating.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the output elements (totals, categories, price range, average rating), which is transparent. However, it does not mention potential performance implications or data freshness, which would be beneficial for a summary tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. Every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although no output schema is provided, the description enumerates the key output fields (totals, categories, price range, average rating), which is adequate for a summary tool. It could specify the structure or format but is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so description need not add parameter info. Baseline 4 is appropriate; the description does not need to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a high-level summary with specific elements: totals, categories, price range, average rating. This distinguishes it from sibling tools like getCategories (only categories) and getPriceStats (only price stats).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a broad overview but does not explicitly state when to use this tool versus sibling tools like getCategories or getPriceStats. No when-not or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Updates a product by id. Note: fakestoreapi.com simulates writes and does not persist them.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| image | No | ||
| price | No | ||
| title | No | ||
| category | No | ||
| description | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It discloses that writes are simulated and not persisted, which is important. However, it omits other behavioral traits like required permissions, rate limits, or side effects beyond non-persistence.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. The first sentence states the purpose, and the second adds a critical note. It is front-loaded and avoids waste, but could include parameter information without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and 6 undocumented parameters, the description is incomplete. It does not explain return values, error handling, required parameters beyond id, or parameter usage. The simulation note is helpful but insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning no parameter details are provided in the description. Despite having 6 parameters, the description adds no meaning beyond the schema field names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Updates a product by id', specifying the action and resource. While it doesn't explicitly differentiate from siblings, the sibling set consists mostly of getter tools, so the purpose is distinct enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description lacks any context about prerequisites, filtering, or when to prefer other tools like createProduct or deleteProduct.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v2.0.0compareProductscountProductscreateProductdeleteProductgetCategoriesgetCategoryStatsgetCheapestInCategorygetCheapestProductgetDiscountedPricegetHighestRatedInCategorygetMostExpensiveProductgetMostReviewedProductsgetPriceStatsgetProductByIdgetProductRecommendationsgetProductsgetProductsAbovePricegetProductsBelowPricegetProductsByCategorygetProductsByMinRatinggetProductsByPriceRangegetRandomProductgetTopRatedProductslistProductTitlessearchProductssummarizeCatalogupdateProductMost tools have distinct purposes, but some overlap exists, e.g., getTopRatedProducts vs getMostReviewedProducts vs getProductsByMinRating, and multiple price-filtering tools could cause confusion.
All tool names follow a consistent camelCase verb_noun pattern (e.g., getProductById, createProduct, countProducts), with no mixing of conventions.
27 tools is on the high side; many are specialized queries that could be combined with optional parameters, but each tool serves a clear purpose.
Covers CRUD and a wide range of queries, though lacks a generic sort/filter endpoint and bulk operations; write operations are noted as simulated.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Product search for AI agents: Amazon + Shopify, cart-to-checkout buy path. Pay-per-call, no API key.
Clean product data from any URL. Schema.org + AI extraction. 200 free calls/month.
AI-callable tools for API mocking, testing, monitoring, security, and automation.
Universal AI API Orchestrator — 1,554 tools, 96 services. One install.
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