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WordPress Trac MCP Server

by Jameswlepage
README.md5.38 kB
# WordPress Trac MCP Server A Model Context Protocol (MCP) server that provides AI assistants with comprehensive access to WordPress.org Trac data. Built with TypeScript and deployed on Cloudflare Workers. **🆕 Now with ChatGPT Deep Research support!** ## Overview This MCP server transforms WordPress Trac into an AI-accessible knowledge base, enabling intelligent queries about WordPress development, ticket tracking, and code changes. Features dual architecture supporting both standard MCP clients and ChatGPT's Deep Research requirements. ## Features - **Dual Architecture**: Standard MCP + ChatGPT Deep Research support - Search 60,000+ WordPress tickets by keywords, components, or status - Get detailed ticket information including descriptions, status, and metadata - Access changeset information with full diff content - Monitor recent WordPress development activity - Retrieve project metadata like components, milestones, and priorities - **Intelligent Query Routing**: Automatically detects ticket numbers, revisions, and keywords - **Smart Caching**: Optimizes fetch operations for better performance - WordPress-branded UI with official styling ## Available Tools The server provides two different tool interfaces depending on your client: ### Standard MCP Tools For Claude Desktop, MCP Inspector, and other standard MCP clients: #### searchTickets Search through WordPress Trac tickets with intelligent filtering. ```json { "tool": "searchTickets", "args": { "query": "REST API performance", "limit": 10, "status": "open" } } ``` #### getTicket Retrieve comprehensive information about specific tickets. ```json { "tool": "getTicket", "args": { "id": 59166, "includeComments": true } } ``` #### getChangeset Access detailed information about code commits and changes. ```json { "tool": "getChangeset", "args": { "revision": 55567, "includeDiff": true, "diffLimit": 2000 } } ``` #### getTimeline Monitor recent WordPress development activity. ```json { "tool": "getTimeline", "args": { "days": 7, "limit": 20 } } ``` #### getTracInfo Get organizational data like components and milestones. ```json { "tool": "getTracInfo", "args": { "type": "components" } } ``` ### ChatGPT Deep Research Tools For ChatGPT's Deep Research feature (simplified interface): #### search Intelligent search that automatically routes to the right data based on your query. ```json { "tool": "search", "args": { "query": "block editor performance" } } ``` **Supported query types:** - **Keywords**: `"REST API bugs"`, `"media upload issues"` - **Ticket numbers**: `"#61234"`, `"61234"` - **Changesets**: `"r58504"`, `"58504"` - **Recent activity**: `"recent"`, `"timeline"`, `"latest"` - **Components**: `"Block Editor"`, `"REST API"` #### fetch Get detailed information about a specific item by ID. ```json { "tool": "fetch", "args": { "id": "61234" } } ``` **Supported ID formats:** - Ticket IDs: `"61234"` - Changeset revisions: `"r58504"` ## Installation ### Deploy to Cloudflare Workers ```bash # Clone the repository git clone https://github.com/Jameswlepage/trac-mcp.git cd trac-mcp # Install dependencies npm install # Login to Cloudflare wrangler login # Deploy npm run deploy ``` ### Connect to AI Assistant #### Standard MCP (Claude Desktop, etc.) Add to your `claude_desktop_config.json`: ```json { "mcpServers": { "wordpress-trac": { "command": "npx", "args": ["mcp-remote", "https://your-worker-url/mcp"] } } } ``` #### ChatGPT Deep Research ChatGPT uses a different connection method than Claude Desktop. Follow these steps: 1. **Open ChatGPT Settings** → Go to the **Connectors** tab 2. **Add Server** → Import your remote MCP server directly: ``` https://your-worker-url/mcp/chatgpt ``` 3. **Enable in Composer** → The server will appear in **Composer** > **Deep Research** tool 4. **Add as Source** → You may need to manually add the server as a research source For detailed setup instructions, see: [ChatGPT MCP Documentation](https://platform.openai.com/docs/mcp#connect-in-chatgpt) > **Note**: ChatGPT requires exactly 2 tools (`search` and `fetch`) with simplified schemas. The `/mcp/chatgpt` endpoint is specifically optimized for this requirement. ## Development ### Local Development ```bash # Start development server npm run dev # Test with MCP Inspector npx @modelcontextprotocol/inspector http://localhost:8787/mcp ``` ### Testing ```bash # Run type checking npm run type-check # Run linting npm run lint # Test deployment curl https://your-worker-url/health ``` ## Architecture - **Runtime**: Cloudflare Workers for global edge deployment - **Language**: TypeScript with Zod validation - **Protocol**: Model Context Protocol (MCP) for universal AI compatibility - **APIs**: Public WordPress Trac CSV/RSS endpoints (no authentication required) ## Live Demo **URL**: https://mcp-server-wporg-trac-staging.a8cai.workers.dev ## License This project is licensed under the GNU General Public License v2 or later - see the [GPL License](https://www.gnu.org/licenses/gpl-3.0.en.html#license-text) for details. ## Contributing Contributions are welcome! This server demonstrates how to build production-ready MCP servers with real-world complexity and WordPress integration.

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