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MCP-researcher Server

MCP-researcher Server

by clssck
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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find_apis

Discover and assess APIs for project integration based on specific functionality requirements and project context.

Instructions

Find and evaluate APIs that could be integrated into a project

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "requirement": "<requirement>"
    },
    "name": "find_apis"
  }
}

Input Schema

NameRequiredDescriptionDefault
requirementYesThe functionality or requirement you're looking to fulfill
contextNoAdditional context about the project or specific needs

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the purpose. It doesn't mention whether the tool performs live searches, what evaluation criteria are used, what output format is returned, or any side effects. This is a significant lack of transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that is front-loaded and directly conveys the tool's purpose. Every word earns its place, and there is no unnecessary detail or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description should compensate by explaining return values, research process, or usage context. It does none of this, leaving the agent without a clear picture of the tool's output, behavior, or when to choose it over siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes both parameters (requirement and context) with 100% coverage, so the baseline is 3. The tool description adds no additional meaning beyond the schema; it doesn't explain how the parameters influence behavior or results.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool finds and evaluates APIs for project integration, using a specific verb and resource. It distinguishes itself from sibling tools like general search and get_documentation, though it doesn't detail the evaluation criteria or depth.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives. It doesn't mention any exclusions, prerequisites, or comparisons with sibling tools like search or get_documentation, leaving the appropriate usage context unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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