Intelligent Documentation Generator MCP Server

An intelligent MCP server that automatically generates and maintains documentation based on code changes, keeping documentation in sync with code while maintaining high quality and comprehensive coverage.

Features

• Intelligent Code Analysis: Automatically analyzes codebases to extract APIs, architecture, configurations, and business logic
• Automatic Documentation Generation: Generates comprehensive documentation based on code changes
• Gap Detection: Identifies missing, outdated, incomplete, or inaccurate documentation
• Quality Assessment: Evaluates documentation quality and provides improvement recommendations
• Smart Updates: Automatically updates documentation when code changes
• Multiple Formats: Supports various documentation formats (Markdown, OpenAPI, Swagger, HTML)

Installation

npm install @gc-mcp/intelligent-documentation-generator

Usage

As MCP Server

npx mcp-doc-generator

Programmatic Usage

import { CodeAnalysisEngine } from "@gc-mcp/intelligent-documentation-generator";

const engine = new CodeAnalysisEngine();
const analysis = await engine.analyzeCode(codeBase);

MCP Tools

1. generate_documentation_intelligence

Intelligently generate documentation based on code changes.

Parameters:

• code_base: Code base information
• changes: List of code changes
• documentation_type: Type of documentation to generate (api, architecture, deployment, configuration, troubleshooting, user_guide)
• target_audience: Target audience (developers, devops, users, stakeholders)
• generation_depth: Depth of generation (basic, detailed, comprehensive)

2. update_documentation_automatically

Automatically update documentation based on code changes.

Parameters:

• changes: List of code changes
• documentation_path: Path to documentation files
• update_strategy: Update strategy (conservative, aggressive, selective)
• review_required: Whether updates require review

3. detect_documentation_gaps

Detect gaps between code and documentation.

Parameters:

• code_base: Code base information
• documentation: Current documentation
• gap_types: Types of gaps to detect (missing, outdated, incomplete, inaccurate)
• coverage_threshold: Minimum coverage threshold

4. suggest_documentation_improvements

Suggest improvements to existing documentation.

Parameters:

• documentation: Current documentation to improve
• improvement_goals: Goals for improvement (clarity, completeness, accuracy, usability, consistency)
• target_audience: Target audience for the documentation
• improvement_scope: Scope of improvements (content, structure, format, all)

5. maintain_api_documentation

Maintain API documentation in sync with code.

Parameters:

• api_changes: List of API changes
• current_documentation: Current API documentation
• documentation_format: Format for API documentation (openapi, swagger, markdown, html)
• include_examples: Include code examples

Configuration

Set the following environment variables:

# Documentation Configuration
DOCUMENTATION_FORMAT=markdown
TEMPLATE_PATH=./templates
OUTPUT_PATH=./docs

# Quality Configuration
QUALITY_THRESHOLD=0.8
AUTO_UPDATE_ENABLED=true
REVIEW_REQUIRED=true

# Analysis Configuration
ANALYSIS_DEPTH=detailed
INCLUDE_EXAMPLES=true
GENERATE_DIAGRAMS=true

Architecture

Core Components

1. Code Analysis Engine: Analyzes codebases to extract structured information
2. Documentation Generator: Generates documentation based on code analysis
3. Gap Detector: Identifies documentation gaps and inconsistencies
4. Quality Assessor: Evaluates documentation quality and provides recommendations
5. Documentation Updater: Automatically updates documentation when code changes

Supported Documentation Types

• API Documentation: REST, gRPC, GraphQL APIs
• Architecture Documentation: Components, relationships, patterns, principles
• Configuration Documentation: Settings, properties, examples
• Deployment Documentation: Installation, configuration, running instructions
• Troubleshooting Documentation: Common issues and solutions
• User Guides: End-user documentation

Quality Metrics

The server assesses documentation quality across multiple dimensions:

• Completeness: Percentage of complete documentation sections
• Accuracy: Average confidence score of documentation sections
• Clarity: Writing clarity and structure assessment
• Consistency: Consistency across documentation sections
• Usability: Navigation, searchability, and user experience

Examples

Generate API Documentation

const result = await mcpServer.callTool("generate_documentation_intelligence", {
  code_base: {
    controllers: [
      {
        name: "UserController",
        methods: [
          {
            path: "/users",
            method: "GET",
            description: "Get all users",
          },
        ],
      },
    ],
  },
  changes: [
    {
      type: "api",
      file: "src/controllers/user.ts",
      description: "Added new user endpoints",
      impact: "medium",
      affectedComponents: ["UserController"],
      breakingChange: false,
    },
  ],
  documentation_type: "api",
  target_audience: "developers",
  generation_depth: "detailed",
});

Detect Documentation Gaps

const result = await mcpServer.callTool("detect_documentation_gaps", {
  code_base: {
    apis: [{ name: "UserAPI", sourceFiles: ["src/api/user.ts"] }],
  },
  documentation: {
    sections: [
      {
        type: "api",
        title: "UserAPI Documentation",
        content: "API documentation content",
      },
    ],
  },
  gap_types: ["missing", "outdated"],
  coverage_threshold: 0.8,
});

Development

Setup

git clone <repository>
cd packages/intelligent-documentation-generator
npm install

Build

npm run build

Test

npm test

Lint

npm run lint

License

MIT

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

Support

For issues and questions, please open an issue on the repository.