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    Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.
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    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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    Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.
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    MIT
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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.
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    MIT
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    A Model Context Protocol server that enables AI assistants to interact with Google Gemini CLI, allowing them to leverage Gemini's large token window for analyzing files and codebases using natural language commands.
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    MIT
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    A lightweight, self-hosted MCP server that connects LLM-based agents to Red Hat Lightspeed services, enabling natural language querying of read-only (and optionally write) operations across Advisor, Image Builder, Inventory, Planning, Remediations, and Vulnerability services.
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    Apache 2.0