When building MCP-based platforms, testing usually means manually crafting JSON-RPC requests or writing custom clients.
I built MCP Smoke as a lightweight test harness where you can:
Send real MCP requests using plain English
Simulate real user/agent interactions
Test tools, prompts, and resources end-to-end
Plug in API keys and hit actual MCP servers
It’s useful if you're building MCP platforms and want:
Faster iteration during development
Realistic testing instead of mocked flows
Observability/analytics on how your MCP server behaves
Would love feedback on what kind of test scenarios or validations should be added.
A comprehensive Prometheus metrics exporter for Gunicorn WSGI servers with support for multiple worker types and advanced monitoring capabilities, featuring innovative Redis-based storage, YAML configuration support, and advanced signal handling. This Gunicorn worker plugin exports Prometheus metrics to monitor worker performance, including memory usage, CPU usage, request durations, and error tracking (trying to replace https://docs.gunicorn.org/en/stable/instrumentation.html with extra info). It also aims to replace request-level tracking, such as the number of requests made to a particular endpoint, for any framework (e.g., Flask, Django, and others) that conforms to the WSGI specification.