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Documentation MCP Server

Documentation MCP Server

by ThaLoc0one
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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docs_analyze_project

Analyzes project structure and performs deep code analysis using language-specific AST parsers to generate documentation for multi-language projects.

Instructions

Analyze project structure and perform deep code analysis to understand the project for documentation generation. Supports TypeScript, JavaScript, Python, Go, and more. Deep analysis extracts classes, functions, interfaces, documentation coverage, and more.

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": {
      "projectPath": "<projectPath>"
    },
    "name": "docs_analyze_project"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectPathYesPath to the project directory to analyze
languageNoPrimary programming language (typescript, javascript, python, go, etc.)
deepNoEnable deep code analysis using language-specific AST parsers (default: true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Discloses deep code analysis using AST parsers and extraction of classes, functions, interfaces, etc. Lacks explicit statement that it is read-only, but no annotations are provided, so description carries full burden.

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?

Two concise sentences that front-load the purpose and follow with capabilities. No redundant or filler content.

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?

Describes inputs and high-level output (extracted elements), but lacks description of return format or how results are presented. Without an output schema, more detail on output would improve completeness.

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% with descriptions for all three parameters. Description adds context about extracted elements (classes, functions, etc.) but does not significantly elaborate on parameter behavior beyond schema.

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?

Clearly states it analyzes project structure and code for documentation generation, listing supported languages and extraction capabilities. Distinguishes well from sibling tools like docs_generate_api or docs_build_static.

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?

Implied usage from context ('for documentation generation'), but no explicit when-to-use vs. alternatives. Does not mention when not to use or prerequisites.

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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