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    An MCP server that allows coding agents to look up contextual rules and patterns on demand, providing just-in-time guidance for specific tasks like writing tests or authoring UI.
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    Provides GitHub Copilot with 160+ AI agent personas and 1,400+ specialized skills, enabling developers to activate expert roles like backend architect or security engineer through natural language.
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    MIT
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    Enables LLMs to apply Martin Fowler's 71+ refactoring patterns to codebases through a pluggable, language-agnostic architecture. Supports previewing and applying refactorings, analyzing code smells, and inspecting code structure with safe-by-default operations.
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    MIT
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    A robust, language-agnostic Model Context Protocol (MCP) server that provides AI coding agents with the ability to edit files surgically via Abstract Syntax Trees (AST) instead of relying on token-heavy, brittle search-and-replace or diff operations.
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    MIT
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    MCP server for TNL (Typed Natural Language): per-feature English contracts for AI coding agents. 6 tools — get_impacted_tnls, retrieve_tnl, trace, propose_tnl_diff, approve_tnl_diff, verify — let agents look up relevant contracts, propose contract edits, and verify implementations against them. Drop-in via npx typed-nl init for Claude Code, Codex, Gemini.
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    MIT
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    Connects AI coding agents to a shared knowledge base by allowing them to search, retrieve, and contribute coding traces. It acts as a protocol adapter for the CommonTrace API, facilitating collaborative knowledge sharing through natural language queries and tool-based interactions.
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    Apache 2.0
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    A fully featured coding agent that uses symbolic operations (enabled by language servers) and works well even in large code bases. Essentially a free to use alternative to Cursor and Windsurf Agents, Cline, Roo Code and others.
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    MIT
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    An MCP server for Trae AI that enables automated creation and management of OpenSpec-compliant projects through natural language descriptions. It features tools for generating specification files, optimizing existing code based on specs, and deploying project templates without command-line intervention.
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    MIT
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    Connects AI coding agents to Autodesk Fusion 360 for CAD automation, enabling natural language control over sketching, 3D modeling, and CAM operations. It uses a Python-based bridge and a custom add-in to execute over 80 tools ranging from simple geometry creation to complex assembly and parameter management.
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    MIT
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    Enables AI-powered code editing with preview and validation capabilities through FastApply language models. Features automatic backups, atomic file operations, and support for multiple FastApply-compatible backends like LM Studio and Ollama.
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    MIT