Guides AI agents through open-source contribution workflows, from finding issues to submitting PRs, while keeping decision-making and coding with the human contributor.
An orchestrator MCP server that takes a plain-language app description and guides agents through a full workflow from intake to deployment, including design, audit, and maintenance.
Open source contribution manager — tracks PRs across repos, discovers contributable issues, diagnoses CI failures, and drafts maintainer responses. 21 MCP tools, 5 resources, 3 prompts. Ships
as CLI, MCP server, and Claude Code plugin.
This server integrates with Mozilla Developer Network (MDN) documentation to suggest CSS properties, check browser support, and provide implementation guidance with user consent mechanisms.
A comprehensive MCP server that enables Claude to read, create, edit, and generate code from Figma designs. Supports design tokens, code generation to multiple frameworks, and accessibility checks.
A starter kit for building Model Context Protocol servers that enables AI tools to access external data and functionalities like checking holidays, disk space, timezones, RSS feeds, code diffs, and web performance metrics.
Enables interaction with Legado Web API via MCP, allowing AI-assisted debugging and management of book sources, RSS sources, replace rules, books, and other Legado features.
Standalone Postgres MCP server with schema-aware indexing, offering 53 query, schema, context, performance, write, and admin tools. Read-only by default and installable across clients.
A Model Context Protocol (MCP) server for Specifai project integration and automation with any MCP-compatible AI tool. This server currently exposes tools to read all documents generated by the Specifai project.
A Model Context Protocol (MCP) server for ROS 2 that enables GitHub Copilot and other AI agents to interact with ROS 2 systems. This server provides tools for monitoring, debugging, and managing ROS 2 nodes, topics, services, and TF2 frames.
Exposes CodeScene's Code Health analysis as local AI-friendly tools, enabling AI assistants to provide insights on code quality, maintainability, and technical debt directly from the codebase.