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    An open-source AI-powered development assistant that connects Claude Desktop to your codebase via MCP, enabling semantic code search, AI-assisted editing, and persistent memory without additional subscriptions.
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    47
    Apache 2.0
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    Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.
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    MIT
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    This is a powerful Model Context Protocol (MCP) server that integrates multiple AI coding agents—Anthropic Claude Code, OpenAI Codex, and Google Gemini—directly into your workflow. It enables seamless cross-provider analysis, leveraging Gemini's massive token window, Codex's specialized coding capabilities, and Claude's advanced reasoning.
    Last updated
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    MIT
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    Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.
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    512
    MIT
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    Enables Claude Code to dispatch opencode CLI tasks as background processes with immediate task handle return, status polling, and result retrieval, avoiding tmux and log parsing issues.
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    Official implementation of Anthropic's 'think' tool that provides Claude with a dedicated space for structured reasoning, improving performance by up to 54% on complex tasks requiring multi-step problem solving.
    Last updated
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    MIT
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    Provides token-efficient code retrieval for coding agents by indexing repositories and enabling ranked snippet search, symbol outlines, and surgical line reads.
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    MIT
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    Provides autonomous codebase exploration through a plan-execute-reflect-report pipeline, generating onboarding reports with file:line references. Exposes both a high-level investigation tool and low-level read-only file access tools via MCP.
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    MIT
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    Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.
    Last updated
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    4,216
    AGPL 3.0
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    * taniwhaai/arai 🦀 🏠 🍎 🪟 🐧 - Policy enforcement for AI coding agents derived from existing instruction files (CLAUDE.md, .cursorrules, .windsurfrules, .github/copilot-instructions.md) — no separate YAML to maintain. Rules with prohibitive predicates (never, forbids, must_not) emit permissionDecision: deny to block tool calls in Claude Code; advisor
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    Apache 2.0
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    An enhanced sequential thinking tool optimized for programming tasks that helps break down complex coding problems into structured, self-auditing thought steps with branching and revision capabilities.
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    MIT