#Task Completion MCP Servers

Forces AI agents to reflect on task execution, matching prompt requirements to actual changes, verifying logs, and declaring gaps before claiming completion.

An AI was asked to build 5 API endpoints, write tests, and update documentation. It built 3 endpoints, left TODO comments in the tests, never touched the documentation, and declared 'Done! Let me know if you need anything else.' The user spent 40 minutes finding the gaps. This happens every single day, on every LLM, in every coding session. This tool forces five completion axes: requirement extraction, completion evidence, gap identification, continuation execution, and final verification against the original request.