echo-server.add
Add two numbers
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First number | |
| b | Yes | Second number |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | No | Response from the tool |
Add two numbers
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First number | |
| b | Yes | Second number |
| 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 claims a simple arithmetic operation ('Add two numbers'), but the annotations declare destructiveHint=true. This directly contradicts the benign read/compute behavior implied by the description, and no side effects are disclosed. This is an annotation contradiction.
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 only three words and contains no filler or redundancy. It is efficiently sized for a trivial operation, though its brevity leaves out behavioral context that would make it more useful.
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 tool marked as destructive, the description is incomplete: it does not explain what side effects occur, whether data is modified, or what the tool returns. An output schema exists, so return values need not be described, but the destructive nature and lack of usage guidance remain significant 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?
The input schema already documents both parameters with 100% coverage, so the description adds no additional meaning about types, formats, or edge cases. The baseline of 3 applies because the schema carries the full semantic weight.
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 operation: adding two numbers, with the operands implied by the schema. It distinguishes itself from the sibling echo-server.echo by naming a concrete arithmetic action, though it does not explicitly contrast itself with any sibling tool.
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?
There is no guidance about when to use this tool versus alternatives, nor any mention of prerequisites or exclusions. The intended use is only implied by the name and one-line description, which is not enough to route an agent confidently.
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.