@SrGrace
Basic information
My Projects Repo for MCP (Model Context Protocol)
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
mcp‑projects is an open‑source repository of example projects that demonstrate the Model Context Protocol (MCP). It provides reusable MCP server and client code, along with integration examples for IBM watsonx.ai and Tavily, and is intended for developers learning or implementing context‑aware AI systems.
Clone the repository, install the required Python packages (e.g., mcp, fastapi, llama-index, etc.) with pip, create a .env file with credentials for IBM watsonx and Tavily, then run the MCP servers first and the clients afterward. The project is designed to be agnostic to the LLM provider with minor changes.
MCP is a standardized way for applications to provide AI models with richer context about their environment, user preferences, and conversation history, solving the problem of limited “working memory” in AI systems.
The projects require Python packages such as `mcp`, `fastapi`, `uvicorn`, `fastapi-mcp`, `llama-index`, `llama-index-embeddings-huggingface`, `llama-index-llms-langchain`, `langchain-mcp-adapters`, and `mcp-use`, installed via pip.
Create a `.env` file in the root folder with the following credentials: `API_KEY`, `PROJECT_ID`, `IBM_CLOUD_URL`, `MODEL_ID` (for IBM watsonx.ai), and `TAVILY_API_KEY` (for web search).
Yes, the projects are agnostic to the LLM provider, though a few code changes are needed to adapt to a different provider.
Always run the MCP servers first, and only then run the clients.
YC (S26) | Open Computer History | Continuously record your company computer work, map your workflows, help you find work worth automating, and power your agents' context
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,
Soar Flight Booking MCP is a remote MCP server available at https://mcp.soar.flights.
Free moving quotes for AI agents from Next Generation Movers, a licensed interstate mover (USDOT 3764697). US long-distance nationwide and local DC/MD/VA. Indicative ballpark price and booking options; optional $0.01 x40
🚀 The fast, Pythonic way to build MCP servers and clients.
Comments