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Streamable Http

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A step-by-step guide and complete working example for building and running an MCP server with streamable HTTP transport using Python, mcp, and FastAPI, enabling

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About

A step-by-step guide and complete working example for building and running an MCP server with streamable HTTP transport using Python, mcp, and FastAPI, enabling AI assistants to access tools over HTTP.

README

📝 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. You’ll 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

📁 Folder Structure

.
├── docs/                        # Diagrams and assets (e.g., mcp-client-server.png)
├── fastapi_example/            # Example mounting multiple MCP servers in FastAPI
│   ├── echo_server.py          # A server exposing a simple echo tool
│   ├── math_server.py          # A server exposing a math tool
│   └── server.py               # FastAPI app that mounts both echo and math servers
├── .gitignore
├── .python-version             # Python version (for tools like pyenv or uv)
├── pyproject.toml              # Project config and dependencies
├── readme.md                   # You're here!
├── runtime.txt                 # Python runtime for platforms like Render
├── server.py                   # Basic standalone MCP server using Tavily search
├── uv.lock                     # Lockfile for uv dependency manager

🛠 Quickstart

  1. Install uv (recommended Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh
  1. Install dependencies and set up environment
uv venv && source .venv/bin/activate
uv pip install -r pyproject.toml
  1. Run the basic MCP server This uses the Tavily API to expose a simple web_search tool.
uv run server.py
  1. Run the FastAPI app with multiple MCP servers
uv run fastapi_example/server.py

This will mount:

🧪 Debug with MCP Inspector

  1. Install CLI support
uv add 'mcp[cli]'
  1. Launch the inspector
uv run mcp dev server.py

Then go to: http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=...

🔌 Connect to Cursor

In Cursor, add your MCP server under Chat Settings > MCP Servers:

{
  "mcpServers": {
    "tavily": {
      "url": "http://localhost:8000/mcp/"
    }
  }
}

✅ Note: You must include the trailing / in the URL.

from github.com/alejandro-ao/mcp-streamable-http

Install Streamable Http in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install mcp-streamable-http

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add mcp-streamable-http -- uvx mcp-remote

FAQ

Is Streamable Http MCP free?

Yes, Streamable Http MCP is free — one-click install via Unyly at no cost.

Does Streamable Http need an API key?

No, Streamable Http runs without API keys or environment variables.

Is Streamable Http hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install Streamable Http in Claude Desktop, Claude Code or Cursor?

Open Streamable Http on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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