Used to install the uv package manager, which is recommended for setting up the MCP server environment
Allows mounting multiple MCP servers in a FastAPI application, enabling organization of different tool sets as separate endpoints
The MCP server implementation is built using Python, with support for Python version management tools like pyenv
Supports deployment on the Render platform through runtime.txt configuration
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Server Examplesearch for the latest AI advancements in healthcare"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Servers over Streamable HTTP β Step-by-Step Guide
π Read the full article here: MCP Servers over Streamable HTTP (Step-by-Step)
This repository contains a complete, working example of how to build and run an MCP (Model Context Protocol) server using Python, mcp, and FastAPI. Youβll learn how to:
Expose tools and functions over HTTP using the MCP protocol
Connect those tools to AI assistants like Cursor
Use streamable HTTP as the transport
Mount multiple MCP servers in a FastAPI app
π Folder Structure
.
βββ docs/ # Diagrams and assets (e.g., mcp-client-server.png)
βββ fastapi_example/ # Example mounting multiple MCP servers in FastAPI
β βββ echo_server.py # A server exposing a simple echo tool
β βββ math_server.py # A server exposing a math tool
β βββ server.py # FastAPI app that mounts both echo and math servers
βββ .gitignore
βββ .python-version # Python version (for tools like pyenv or uv)
βββ pyproject.toml # Project config and dependencies
βββ readme.md # You're here!
βββ runtime.txt # Python runtime for platforms like Render
βββ server.py # Basic standalone MCP server using Tavily search
βββ uv.lock # Lockfile for uv dependency managerβΈ»
π Quickstart
Install uv (recommended Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | shInstall dependencies and set up environment
uv venv && source .venv/bin/activate
uv pip install -r pyproject.tomlRun the basic MCP server This uses the Tavily API to expose a simple web_search tool.
uv run server.pyRun the FastAPI app with multiple MCP servers
uv run fastapi_example/server.pyThis will mount:
http://localhost:8000/echo/mcp/
http://localhost:8000/math/mcp/
βΈ»
π§ͺ Debug with MCP Inspector
Install CLI support
uv add 'mcp[cli]'Launch the inspector
uv run mcp dev server.pyThen go to: http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=...
βΈ»
π Connect to Cursor
In Cursor, add your MCP server under Chat Settings > MCP Servers:
{
"mcpServers": {
"tavily": {
"url": "http://localhost:8000/mcp/"
}
}
}β Note: You must include the trailing / in the URL.
βΈ»
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