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    An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.
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    MIT
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    Runs as an MCP server providing file system operations, shell execution, and system information tools, allowing Claude or any MCP client to edit files and control the machine.
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    MIT
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    Wraps the cursor-agent CLI to provide cost-effective tools for repository analysis, code search, planning, and editing. Offloads heavy thinking tasks from the host AI to reduce token usage while maintaining precise, scoped workspace operations.
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    MIT
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    Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.
    3
    MIT
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    A local project intelligence, batch coding, and self-learning engine for Codex that enables task-level batch coding, reduces token usage, and automatically learns skills.
    Apache 2.0
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    MCP server that lets Claude, ChatGPT, or VS Code build a complete, machine-checked model of your domain and generate an app from it.
    Apache 2.0
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    Bridges Codex to a local Claude Opus 5 collaborator via Claude Code, enabling controlled read-only consultation or write-capable tasks on allowed workspaces with independent verification.
    MIT
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    Enables AI harnesses to run iterative loops on code repositories with built-in quality evaluations, security gates, and approval workflows for tasks like fixing tests or implementing features.
    27
    MIT
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    Implements Agentic Context Engineering to create self-improving AI coding assistants that learn from execution feedback and build persistent knowledge playbooks. Reduces token usage by 86.9% while improving code accuracy by 10.6% through incremental context updates.
    4
    MIT
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    Enables coding agents like Cursor to access Figma design data, fetch layout and styling information, and implement designs in any framework.
    94,922
    MIT
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    Provides file caching and diff tracking for AI coding agents, reducing token usage by returning changes or confirming no changes instead of full file contents on repeated reads.
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    MIT
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    https://gopls-mcp.org/ MCP server for golang projects development: Expand AI Code Agent ability boundary to have a semantic understanding and determinisic information for golang projects.
    57
    BSD 3-Clause
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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.
    MIT
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    Forwards normalized MCP tools to Codex or Claude Code for agentic coding tasks like starting new sessions, continuing existing ones, and checking status.
    1
    MIT