Create a new post
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | Post body | |
| title | No | Post title | |
| userId | No | User ID |
| Name | Required | Description | Default |
|---|---|---|---|
| result | No | Response from the tool |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description contradicts the annotations. The annotation declares destructiveHint=true, but 'Create a new post' implies an additive, non-destructive operation. This is a significant inconsistency that could mislead an agent into expecting destructive side effects. The description adds no behavioral context beyond the annotations, and what it does imply conflicts with them.
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 concise for a simple creation tool. While it could include more structural detail like parameter prerequisites, the brevity itself is not a flaw; it communicates the core purpose efficiently.
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 and has an output schema, so return values are likely covered. However, the description lacks any usage guidance or context about when to call it, and it omits any mention of optional/required parameters. For a basic create operation with fully documented params, this is adequate but not comprehensive.
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 provides descriptions for all three parameters (body, title, userId), achieving 100% schema description coverage. The tool description adds no additional parameter semantics. Per the rubric, the baseline is 3 when schema coverage is high, and that is appropriate here.
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 'Create a new post' clearly states the verb (create) and the resource (post), making the tool's purpose immediately understandable. It distinguishes itself from sibling read-only tools like jsonplaceholder.getPost and getPosts, though it doesn't explicitly differentiate from other create tools like petstore-api.addPet or createUser. The specificity of 'post' is sufficient for 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 is provided on when to use this tool versus alternatives. It does not mention that reading posts uses getPost/getPosts, nor does it mention any prerequisites or conditions for creating a post. The description is a bare statement of function with no situational context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are clearly namespaced by service (e.g., petstore-api, github-api, jsonplaceholder), which reduces cross-service confusion. Within each service, operations are generally distinct (e.g., getPetById vs updatePet). However, some overlap exists like updatePet and updatePetWithForm, and there are multiple 'get' tools across services that could be mixed up in a large set, but descriptions help.
Naming conventions are inconsistent across the set. Some tools use camelCase (github-api.getRepo), others use underscores (acme-mailer.send_email), and some are single simple verbs (echo-server.echo, memory.store). While each service follows its own style, the server as a whole lacks a unified pattern, making the naming chaotic.
With 38 tools, this server is heavily overloaded for a typical MCP scope. The tools span ten different services, indicating a broad aggregation rather than a focused purpose. This exceeds the recommended 3-15 tool range and even the 25+ threshold, making it feel like a collection of unrelated utilities.
The domain is unclear, but looking at each sub-service, most are incomplete. For example, github-api only offers read operations (no create/update/delete), jsonplaceholder has posts CRUD but only get for users, and open-weather lacks historical data. Memory and echo-server are trivial. The surface does not fully cover any single domain, leaving significant gaps for agent workflows.