SDK MCP Server

A configurable Model Context Protocol (MCP) server that provides searchable access to multiple AI/ML SDK documentation and source code. Currently supports OpenAI Agents SDK and Google ADK, with easy extensibility for additional SDKs.

Purpose

When working with AI/ML SDKs, you often need to:

• Understand how classes and methods work internally across different SDKs
• Compare implementations between different frameworks
• Find the right method signatures and parameters
• See real implementation examples
• Debug issues by examining SDK source code

This MCP server gives AI assistants like Claude instant access to multiple SDK sources, making it a powerful development companion for multi-SDK projects.

Quick Start

1. Install dependencies:

pip install -r requirements.txt

2. Download SDK sources:

python src/download_sdk.py

This will download all configured SDKs from sdks.yaml.

3. Configure in Claude Desktop:

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "sdk-mcp-server": {
      "command": "python",
      "args": ["/absolute/path/to/sdk-mcp-server/src/server.py"]
    }
  }
}

Available Tools

Each configured SDK gets its own set of tools with the SDK prefix. Currently configured:

OpenAI Agents SDK Tools (prefix: openai_agents_)

• openai_agents_list_files() - List all available OpenAI SDK source files
• openai_agents_get_source(filename) - Get source code of specific file
• openai_agents_search_code(query) - Search for terms, methods, or patterns
• openai_agents_get_class(class_name) - Extract complete class definition
• openai_agents_find_examples(topic) - Find usage examples and patterns

Google ADK Tools (prefix: google_adk_)

• google_adk_list_files() - List all available Google ADK source files
• google_adk_get_source(filename) - Get source code of specific file
• google_adk_search_code(query) - Search for terms, methods, or patterns
• google_adk_get_class(class_name) - Extract complete class definition
• google_adk_find_examples(topic) - Find usage examples and patterns

Cross-SDK Tools (coming soon)

• list_available_sdks() - Show all configured SDKs
• search_all_sdks(query) - Search across all SDKs simultaneously
• compare_implementations(concept, sdk_ids) - Compare similar concepts across SDKs

Usage Examples

Comparing SDKs:

You: "How do OpenAI and Google handle agent creation differently?"
Claude: [Uses openai_agents_get_class("Agent") and google_adk_get_class("Agent")]
*Compares the different approaches and APIs*

Learning a new SDK:

You: "Show me how to use tools in Google ADK"
Claude: [Uses google_adk_search_code("tool") and google_adk_find_examples("tool")]
*Explains Google's approach with real examples*

Debugging across SDKs:

You: "Why does handoff work in OpenAI but not in my Google ADK code?"
Claude: [Searches both SDKs for handoff implementations]
*Identifies the differences and helps fix the issue*

Configuration

Adding a New SDK

Edit sdks.yaml to add new SDKs:

sdks:
  your_sdk:
    name: "Your SDK Name"
    description: "Description of the SDK"
    source:
      type: "github"
      repo: "org/repo-name"
      branch: "main"
      path: "src"
    file_patterns:
      - "**/*.py"
    tools:
      prefix: "your_sdk"
      descriptions:
        list_files: "List all Your SDK source files"
        # ... other tool descriptions

Supported Source Types

• GitHub repositories - Public repos with Python/TypeScript code
• Direct URLs (coming soon) - ZIP/TAR archives
• Local paths (coming soon) - Local SDK installations

File Structure

sdk-mcp-server/
├── src/
│   ├── server.py           # Main MCP server implementation
│   └── download_sdk.py     # SDK downloader and indexer
├── data/                   # Downloaded SDK files (git-ignored)
│   ├── openai_agents/      # OpenAI SDK files
│   └── google_adk/         # Google ADK files
├── sdks.yaml              # SDK configuration
├── requirements.txt       # Python dependencies
└── run_server.sh         # Server startup script

Updating

To get the latest SDK sources:

python src/download_sdk.py

This fetches the latest code from all configured SDKs in sdks.yaml.

Tips for Best Results

1. Specify the SDK - Mention which SDK you're working with
2. Use SDK prefixes - Each tool is prefixed with the SDK name
3. Compare implementations - Ask about differences between SDKs
4. Request examples - Each SDK has example-finding capabilities

Why This Helps

• Multi-SDK support - Work with multiple frameworks seamlessly
• Instant answers - No need to browse multiple repos or docs
• Direct comparisons - See how different SDKs solve similar problems
• Accurate information - Always from the latest source code
• Context-aware - AI understands full implementations across SDKs

Contributing

To add support for a new SDK:

1. Add configuration to sdks.yaml
2. Test with python src/download_sdk.py
3. Submit a pull request

License

MIT License - see LICENSE file for details.