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get_mcp_details

Read-onlyIdempotent

Get complete details for a specific MCP server: description, use cases, tools, install configs.

Args:
    slug: MCP server slug.

Returns:
    Full MCP record with description, long description, use_cases (list of scenarios),
    tools (what the server exposes), install_configs (per-client snippets),
    license, author, stars, page_url.

Use this when the user wants to learn more about a specific MCP before installing,
or when they ask "what does X MCP do" or "show me use cases for X".

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": {
      "slug": "<slug>"
    },
    "name": "get_mcp_details"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesMCP server slug - take it from the `slug` field of search_mcp_servers results, e.g. "github-mcp".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent and non-destructive, so the description's strongest contribution is spelling out that this returns a rich single record (use_cases, tools, install_configs, license, author, stars, page_url). Missing only edge behavior such as what happens on an unknown slug 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.

Conciseness4/5

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

Front-loaded one-line summary, then Args/Returns/When-to-use in a predictable docstring layout that is easy to scan. The Args section is largely redundant with the schema, a small amount of avoidable bulk.

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

Completeness4/5

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

With no output schema, describing the returned fields is genuinely necessary and is done well; the usage triggers round it out. An error path for invalid slugs and an explicit pointer that slug comes from search_mcp_servers would make it fully self-sufficient.

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?

Schema coverage is 100% and the schema already explains the slug and where to obtain it from search results. The description's 'Args: slug: MCP server slug' restates that without adding format or sourcing detail, so baseline 3 applies.

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

Purpose5/5

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

States a specific verb and resource ('Get complete details for a specific MCP server') and enumerates the payload (description, use cases, tools, install configs), which cleanly separates it from siblings such as get_mcp_install_config or search_mcp_servers.

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

Usage Guidelines4/5

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

Gives concrete triggering conditions plus sample user phrasings ('what does X MCP do', 'show me use cases for X'), so the agent knows when to reach for it. It stops short of naming alternatives or exclusions, e.g. deferring to get_mcp_install_config when only snippets are needed.

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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