MCP Streamable HTTP Python Server

MCP Streamable HTTP Python Server is an open-source development template that implements the Model Context Protocol over a streamable HTTP transport layer using Python. It connects LLM client applications to custom server-side functions and tools over standard network protocols rather than local standard input and output streams. Designed for developers building custom AI tools, remote microservices, or external integrations, it provides a functional starting architecture based on the official MCP Python SDK quickstart patterns. By using the streamable HTTP transport specification introduced in early 2025, the server allows clients like Claude Desktop and other MCP-compatible hosts to establish HTTP-based communication with running Python processes. Developers can clone the repository, add custom endpoints or tool handlers, configure port numbers, and run the service locally or within containerized environments. It simplifies bootstrapping remote or local HTTP MCP tools without requiring developers to write connection handling or low-level transport mechanisms from scratch.

Category: AI & LLM Tooling

Tags: http, python, streaming, template

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How to install and configure MCP Streamable HTTP Python Server

1. Clone or fork the repository from https://github.com/ferrants/mcp-streamable-http-python-server. 2. Create and activate a Python virtual environment: bash python3.11 -m venv my_env . ./my_env/bin/activate 3. Install the dependencies: bash pip install -r requirements.txt 4. Start the server directly or specify a custom port: bash python server.py # or with a custom port: PORT=3002 python server.py 5. Connect your MCP client using an HTTP streamable entry in your MCP configuration file (for example, mcp-config.json): json { "mcpServers": { "memvid": { "type": "streamable-http", "url": "http://localhost:3000" } } }

What you can do with MCP Streamable HTTP Python Server

• Bootstrapping a custom Python-based MCP server using the streamable HTTP transport specification instead of stdio. - Exposing local Python data analysis scripts or utilities to remote or local AI clients over network ports. - Testing MCP client connections against an independent local HTTP endpoint during AI development workflows. - Serving AI agent tools across microservices or containerized infrastructure where standard input/output transport is impractical.

Key facts

• Open Source
• https://github.com/ferrants/mcp-streamable-http-python-server
• AI & LLM Tooling
• http, python, streaming, template

Part of MCP Servers

How do I install MCP Streamable HTTP Python Server?

To install it, clone the repository to your local system, set up a Python 3.11 virtual environment, activate it, and run pip install -r requirements.txt. Once dependencies are installed, start the application by running python server.py.

What can MCP Streamable HTTP Python Server do?

The server provides a starter template for running an MCP server over streamable HTTP transport. It allows developers to register custom Python functions, handle agent tool calls, and expose services to compatible AI clients over standard network ports.

Which MCP clients work with MCP Streamable HTTP Python Server?

Any MCP client that supports network-based streamable HTTP connections can interface with this server. Clients are configured by adding an entry pointing to the running server URL, such as http://localhost:3000, in the client configuration file.

Is MCP Streamable HTTP Python Server open source?

Yes, MCP Streamable HTTP Python Server is open-source software available for developers to clone, fork, and customize on GitHub at https://github.com/ferrants/mcp-streamable-http-python-server.