Launching today
SineFrame M3
Test MCP servers and the agents that call them in pytest
11 followers
Test MCP servers and the agents that call them in pytest
11 followers
Your MCP unit tests pass, but did the agent call the tool? M3 runs your server through real Claude Code, Codex, OpenCode or Pi and asserts on the calls they actually made, in plain pytest. Direct tests need no API key. m3 ui shows every trace and tool call; m3 ci test --upload gates PRs and keeps runs on app.m3.sineframe.com. Open source, Apache-2.0.
Free
Launch Team
World model AI : Sharm SEKAISimulate your idea on a living world.
Promoted
Hey Product Hunt 👋 This is Rishav and Utkarsh, and we built SineFrame M3.
Here's the gap we kept hitting: your MCP server's unit tests pass, then a real agent answers from memory, picks the wrong tool, or calls it with the wrong arguments. Nothing in the test suite sees it.
M3 is pytest for that gap:
🔌 Direct tests: call your server over stdio or Streamable HTTP and assert on the structured results. No model, no API key.
🤖 Agent tests: run real Claude Code, Codex, OpenCode, Pi or any ACP agent against your server, then assert on the tool calls recorded on the wire, not on what the agent says it did.
🔍 m3 ui: every run saved locally, with traces, tool calls, arguments and a timeline.
✅ m3 ci test --upload: the same tests gate your pull requests, and runs land on app.m3.sineframe.com for the team.
How it's different: an inspector is for poking at a server by hand, and eval platforms grade your own LLM app. M3 is test code in your repo that checks your server and the real agents that call it.
Free and open source (Apache-2.0):
uv tool install sf-m3-cli
Free account for hosted runs: sineframe.com
I'm here all day. What's the hardest MCP behavior for you to test today?