Example implementation of MCP Streamable HTTP client/server in Python and TypeScript.
# Add to your Claude Code skills
git clone https://github.com/invariantlabs-ai/mcp-streamable-httpGuides for using mcp servers skills like mcp-streamable-http.
Last scanned: 5/30/2026
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"status": "PASSED",
"scannedAt": "2026-05-30T16:21:29.508Z",
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}mcp-streamable-http is an open-source mcp servers skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by invariantlabs-ai. Example implementation of MCP Streamable HTTP client/server in Python and TypeScript. It has 129 GitHub stars.
Yes. mcp-streamable-http passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/invariantlabs-ai/mcp-streamable-http" and add it to your Claude Code skills directory (see the Installation section above).
mcp-streamable-http is primarily written in TypeScript. It is open-source under invariantlabs-ai on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other MCP Servers skills you can browse and compare side by side. Open the MCP Servers category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh mcp-streamable-http against similar tools.
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This repository provides example implementations of MCP (Model Context Protocol) Streamable HTTP client and server in Python and Typescript, based on the specification: 📄 MCP Streamable HTTP Spec.
You can set up a client + server stack entirely using either Python or TypeScript. This example also demonstrates cross-language compatibility, allowing a Python client to communicate with a TypeScript server, and vice-versa.
git clone https://github.com/invariantlabs-ai/mcp-streamable-http.git
cd python-example
Update the .env file inside the python-example/client directory with the following content:
ANTHROPIC_API_KEY=your_api_key_here
cd python-example/server
pip install .
python weather.py
By default, the server will start at http://localhost:8123.
If you'd like to specify a different port, use the --port flag:
python weather.py --port=9000
cd ../client
pip install .
python client.py
This will start an interactive chat loop using the MCP Streamable HTTP protocol.
If you started the MCP server on a different port, specify it using the --mcp-localhost-port flag:
python client.py --mcp-localhost-port=9000
Update the .env file inside the typescript-example/client directory with the following content:
ANTHROPIC_API_KEY=your_api_key_here
cd typescript-example/server
npm install && npm run build
node build/index.js
By default, the server will start at http://localhost:8123.
If you'd like to specify a different port, use the --port flag:
node build/index.js --port=9000
cd ../client
npm install && npm run build
node build/index.js
This will start an interactive chat loop using the MCP Streamable HTTP protocol.
If you started the MCP server on a different port, specify it using the --mcp-localhost-port flag:
node build/index.js --mcp-localhost-port=9000
In the client chat interface, you can ask questions like:
The client will forward requests to the local MCP weather server and return the results using Anthropic’s Claude language model. The MCP transport layer used will be Streamable HTTP.