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    A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.
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    1
    MIT
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    MCP server connecting Claude/Cursor to Codex CLI, enabling code analysis via @ file references, multi-turn conversations, sandboxed edits, and structured change mode.
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    MIT
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    Official Bright Data server for the Model Context Protocol that enables AI assistants like Claude Desktop to reference and make decisions based on real-time public web data.
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    MIT
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    Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.
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    MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.
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    MIT
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    Enables LLMs to interact with the AT Protocol ecosystem, including Bluesky, through natural language. Supports public data access without authentication and full write operations with authentication.
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    MIT
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    Provides AI assistants with direct access to Jamf official documentation, enabling them to answer Jamf-related questions by searching, retrieving articles, and browsing product documentation.
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    MIT
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    Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.
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    MIT
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    This MCP server provides comprehensive Google Workspace integration (Gmail, Drive, etc.) with multi-user OAuth. Unique features include RAG-powered natural language to Chat card rendering, runtime Jinja2 macro creation, and dynamic tool management.
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    Apache 2.0
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    Enables AI assistants to search live jobs, view full details, save and track applications in a Kanban board, set follow-up reminders, and subscribe to job alerts—no account needed for searching.
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    MIT