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Engineering Documentation MCP Server

Engineering Documentation MCP Server

by mfaizanmumtaz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

generate_readme

Generates a professional README.md from code analysis, including badges, description, installation, usage, and API overview.

Instructions

Generate a professional README.md for a repository based on code analysis. Includes badges, description, installation, usage, and API overview.

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": {
      "repo_path": "<repo_path>"
    },
    "name": "generate_readme"
  }
}

Input Schema

NameRequiredDescriptionDefault
repo_pathYesPath to the repository.
output_pathNoWhere to save the README.md (defaults to repo_path/README.md).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions 'based on code analysis' but does not reveal whether the tool overwrites an existing README, requires special permissions, or performs side effects like writing files. The output_path parameter hints at file creation, but the description itself omits this critical behavioral detail.

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 one sentence that is front-loaded with the core action and resource, followed by a compact list of included sections. Every word earns its place, with no redundancy or unnecessary detail.

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

Completeness3/5

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

For a simple two-parameter tool with an output schema, the description covers the main purpose and output contents. However, it lacks usage guidelines and behavioral transparency (e.g., file overwriting, analysis scope), which are needed for an agent to select and invoke it confidently among sibling documentation tools.

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 description coverage is 100% for both parameters (repo_path and output_path), so the schema already documents their meaning. The description adds no additional parameter semantics beyond mentioning the output content sections. Per the rubric baseline for high schema coverage, a score of 3 is appropriate.

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?

The description clearly states the tool's function: 'Generate a professional README.md for a repository based on code analysis.' It specifies the resource (README.md), the input (repository), and the method (code analysis). This distinguishes it from sibling tools like generate_project_documentation (broader), document_api, and generate_architecture, which target different artifacts.

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

Usage Guidelines3/5

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

The description implies usage for generating READMEs from code analysis but does not explicitly state when to use this tool over alternatives like generate_project_documentation or document_api. There are no exclusions or alternative naming, so the agent must infer context from the sibling list and purpose.

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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