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AI Coding MCP v2

Lightweight MCP server for AI IDEs (Claude Code, Cursor, etc.). Provides 21 tools across 4 modules without LLM wrapping.

Architecture Overview

Quick Start

pip install -r requirements.txt
python server.py

Modules

Context (4 tools)

  • index_project - Index project files and extract symbols
  • get_symbol_info - Look up symbol information
  • get_dependency_graph - Analyze file dependencies
  • get_project_stats - Get project statistics

Knowledge (4 tools)

  • search_docs - Search documentation (stub)
  • get_package_info - Query package registries (PyPI/npm)
  • search_code_examples - Search code examples (stub)
  • check_compatibility - Check dependency compatibility

Workflow (6 tools)

  • git_status - Get git working tree status
  • git_history - Get commit history
  • git_branch_analysis - Analyze branches (stub)
  • ci_status - Check CI status (stub)
  • issue_list - List GitHub issues (stub)
  • pr_summary - Get PR summary (stub)

Specs (6 tools)

  • list_specs - List specification files
  • get_spec - Read spec content
  • search_specs - Search specs
  • create_spec - Create new spec from template
  • scaffold_project - Scaffold project from template
  • validate_structure - Validate directory structure (stub)

Architecture

Data Flow

  • CLI-first: All external calls via git, gh, pip, npm, curl
  • Zero LLM wrapping: Return structured data, let AI IDE analyze
  • File-based cache: TTL cache in ~/.cache/ai-coding-mcp/
  • Pydantic config: Type-safe configuration

Project Structure

ai-coding-mcp/
├── server.py                    # FastMCP entry, tool registration
├── config.py                    # Pydantic config
├── tools/
│   ├── context/                 # code_indexer, dependency_graph, project_stats
│   ├── knowledge/               # doc_search, package_info, code_search, compatibility
│   ├── workflow/                # git_ops, ci_github
│   └── specs/                   # spec_manager, scaffold, validator
├── utils/
│   ├── cli_runner.py            # Unified CLI executor
│   └── cache.py                 # File-based TTL cache
├── tests/
├── requirements.txt
└── README.md

Testing

pytest tests/ -v

IDE Configuration

For Claude Code, add to your MCP settings:

{
  "mcpServers": {
    "ai-coding": {
      "command": "python",
      "args": ["server.py"]
    }
  }
}

License

MIT License

About

基于Model Context Protocol (MCP)的AI编程助手服务器,为开发者提供智能化的应用数据获取和分析服务。

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