This MCP server implements a dynamic search and chunking approach to discovering and aggregating MCP servers into a marketplace. It scrapes unprocessed MCP servers, checks for updates, and keeps the marketplace in sync with changes from the source servers. The server exposes a modular API for querying the available MCP servers, requesting batched chunks of results, and triggering synchronization tasks. Expect features like paginated search results, chunked data retrieval for large marketplaces, and background ETL-style syncing to ensure the marketplace reflects the latest state of registered MCP servers.

Prerequisites:

• Node.js (14.x or newer) and npm installed on your system
• Access to the project repository (clone or download the source)

Installation steps:

1. Clone the repository: git clone https://github.com/user-attachments/nabhag8848-mcp-marketplace.git cd nabhag8848-mcp-marketplace

2. Install dependencies: npm install

3. Configure environment (example): Create a .env file with required variables, e.g.: PORT=3000 NODE_ENV=production

4. Run the server: npm start

   or if a specific script is provided in package.json, use:

   npm run dev

5. Optional: Build for production if the project uses a build step. npm run build

6. Verify the server is running by querying the health endpoint or base URL, for example: curl http://localhost:3000/health

Notes and tips:

• If you encounter port conflicts, change the PORT environment variable in .env or during startup.
• Ensure the crawler/ETL components have network access to source MCP servers and the marketplace database.
• The mcp_config currently uses a Node.js server entry (server.js). If your deployment uses a different entry point, adjust the args accordingly.
• For large marketplaces, leverage the chunked API endpoints to fetch results in batches to reduce memory usage and latency.
• Keep dependencies up to date to avoid breaking changes in the MCP protocol or scraping logic.
• If you need to override defaults, environment variables can be used to tweak search depth, batch sizes, and sync intervals.