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Engineering Documentation MCP Server

Engineering Documentation MCP Server

by mfaizanmumtaz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

analyze_repository

Analyze a software repository to extract detailed metadata including languages, frameworks, API endpoints, database models, environment variables, CI/CD configuration, and dependencies.

Instructions

Analyze a software repository and return detailed metadata including detected languages, frameworks, API endpoints, database models, environment variables, CI/CD configuration, and dependencies.

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": "analyze_repository"
  }
}

Input Schema

NameRequiredDescriptionDefault
repo_pathYesAbsolute or relative path to the repository root directory.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It clearly states the tool analyzes and returns metadata, but it does not explicitly state that it is read-only, nor does it mention behavior for invalid paths or potential performance implications. Core behavior is covered, but edge cases are not.

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, front-loaded sentence that efficiently conveys the purpose and output. The list of metadata categories is informative without being redundant.

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

Completeness5/5

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

Given the low complexity of one parameter and the presence of an output schema, the description adequately covers what the tool does and what it returns. It provides a clear scope of the analysis, making it sufficient for an agent to correctly select and invoke the tool.

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 the sole parameter repo_path, which is fully described as an absolute or relative path. The tool description adds no additional nuance about parameters, so the baseline score of 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?

The description clearly states the tool analyzes a software repository and returns detailed metadata. It lists specific metadata categories (languages, frameworks, API endpoints, etc.), distinguishing it from sibling tools that generate documentation rather than analyze and report.

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 when repository metadata is needed, but it does not explicitly mention when to avoid using it or name any alternative tools. Sibling tools like generate_project_documentation could overlap, but no exclusions are provided.

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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