thedaviddias/Front-End-Checklist
Front-End Checklist is an open-source quality system for modern web development, offering comprehensive best practices for humans and AI agents.
Awesome AI Agents › MCP Server Framework
Overture addresses a common complaint about AI coding agents: they begin editing files immediately, so a misunderstood request is only discovered after hundreds of lines have been written. The tool installs as a Model Context Protocol server and works with any MCP-compatible agent, including Claude Code, Cursor, Cline, GitHub Copilot and Sixth AI, with per-client configuration snippets given in the README. When the agent starts planning, Overture intercepts that phase and opens a local web interface, by default on port 3031, that renders the plan as an interactive graph rather than a block of chat text. The graph makes explicit what plain text hides: which tasks depend on which others, where alternative approaches branch, what files, APIs or secrets each step needs, which steps carry risk, and how far execution has progressed. Users can pan, zoom and click through nodes, attach context such as files, keys or extra instructions to individual steps, and compare the advantages and disadvantages of competing approaches before choosing one. The agent does not write code until the plan is approved. Once execution begins, nodes light up as they complete, so the flowchart doubles as a progress view. A built-in MCP marketplace lets the user browse tools and attach them to specific nodes, scoping capabilities per step instead of granting them globally. Everything runs locally as an npm package, published as overture-mcp and installable through npx or a global install, and the project is MIT licensed with continuous integration on GitHub. It is aimed at developers who use coding agents on non-trivial tasks and want a review gate between the prompt and the diff.
https://github.com/SixHq/Overture
Front-End Checklist is an open-source quality system for modern web development, offering comprehensive best practices for humans and AI agents.
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