Test MCP Server

# test_mcp_server A simple **MCP (Model Context Protocol) server** project demonstrating both **local** and **remote** MCP server setups using **FastMCP**, **LangChain**, and **uv**. ## Requirements * Python 3.9+ * `pip` * `uv` ## First-Time Setup ### 1. Install `uv` ```bash pip install uv ``` ### 2. Navigate to the project directory ```bash cd test_mcp_server ``` ### 3. Initialize the project with `uv` ```bash uv init . ``` ### 4. Add FastMCP ```bash uv add fastmcp ``` ## Local MCP Server Setup ### 1. Create the local server file Create a file named: ```text local_server.py ``` This file contains your MCP server implementation. ### 2. Add required dependencies ```bash uv add langchain langchain-openai langchain_mcp_adapters ``` ### 3. Create the client Create a client file: ```text client.py ``` ### 4. Run the local server using STDIO The local MCP server communicates via **STDIO**. Run the client: ```bash uv run client.py ``` ## Remote MCP Server Setup ### 1. Create MCP tools * Define your MCP tools for the remote server * Ensure they are compatible with FastMCP Cloud ### 2. Deploy to FastMCP Cloud * Deploy the server to **FastMCP Cloud** * Obtain the remote server configuration ### 3. Update configuration * Add the remote MCP server configuration to your config file * Replace the local STDIO setup with the remote server endpoint ### 4. Run the client with the remote server ```bash uv run client.py ``` ## Notes * Local server uses **STDIO** for communication * Remote server runs on **FastMCP Cloud** * `uv` handles dependency management and execution * Same client can be used for both local and remote servers by changing configuration ## Remote MCP Server Deployment (FastMCP Cloud) ### GitHub Access * GitHub repository access was granted to **FastMCP Cloud** * FastMCP Cloud pulls the source code directly from the repository ### Deployment Steps 1. Created MCP tools for the remote server 2. Connected the GitHub repository to **FastMCP Cloud** 3. FastMCP Cloud executed the server using: ```text main.py ``` 4. The server was successfully deployed as a **remote MCP server** ### Client Configuration * Updated the MCP configuration file to point to the remote FastMCP Cloud endpoint * Reused the same `client.py` for both local and remote execution ### Running the Client ```bash uv run client.py ```