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"MCP tools or platforms for code editing" matching MCP servers:

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    MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution
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    MIT
    • Apple
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    Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.
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    Apache 2.0
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    A modular multi-server architecture providing development automation, JIRA management, and performance reporting for Claude Code. It features specialized tools for PR health analysis, code reviews, and generating comprehensive team and individual quarterly reports.
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    A FastMCP server providing powerful code editing tools including precise file modifications with diff-based operations, file creation and reading with line numbers, and more tools for code editing workflows.
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    Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.
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    A local Model Context Protocol (MCP) server that exposes custom tools to Claude Desktop, enabling direct interaction with your local environment. It provides a framework for building and integrating custom TypeScript tools into the Claude interface.
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    A comprehensive MCP server that provides AI assistants with tools for file system management, Git integration, and shell command execution. It features specialized code utilities for analysis, formatting, and linting to enhance development workflows within Claude Desktop.
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    An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.
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    An experimental MCP server that enables AI assistants to interact with VS Code workspaces through file operations, code execution, and Git management. It also provides tools for Docker integration, project scaffolding, and secure command execution using project-specific configurations.
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    Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.
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    Apache 2.0
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    Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.
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    Enables safe, concurrent file system operations with sandboxed directory access control, automatic encoding detection, optimistic locking, and precise code editing capabilities including search-replace and batch operations.
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    A comprehensive MCP server providing tools for AI agents to interact with code, including reading symbols, importing modules, replacing text, and sending OS notifications.
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    A security filter that blocks dangerous code patterns by comparing normalized structural syntax trees against a blacklist of known threats using vector embeddings. It acts as a gatekeeper to prevent malicious code execution by identifying dangerous structures regardless of specific identifiers or literals.
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    Enables comprehensive code analysis including quality assessment, security vulnerability detection, refactoring suggestions, complexity calculations, and automatic documentation generation for multiple programming languages.
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    A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
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    A modular MCP server that provides tools for file operations, regex-based code searching, and structural analysis of functions and classes across multiple programming languages. It also includes AI-powered features for intelligently updating files according to architectural changes.
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    • Apple
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    This project aims to build a Claude Code MCP server and implement its associated tools (explain\_code, review\_code, fix\_code, edit\_code, test\_code, simulate\_command, your\_own\_query). The server is implemented using Node.js and the MCP SDK. It receives tool requests from clients via Stdio, dynamically
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    A smart code retrieval tool based on Model Context Protocol that provides efficient and accurate code repository search capabilities for large language models.
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    Enables LLMs to perform high-performance code search and analysis across multiple languages using symbol indexing, regex text search, and structural AST pattern matching. It also provides tools for technology stack detection and dependency analysis with persistent caching for optimized performance.
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    Standalone MCP server for code structure analysis using tree-sitter. Directory trees, symbol definitions, and call graphs without reading raw source files. Supports Rust, Python, Go, Java, TypeScript, Fortran, JavaScript, C/C++, and C#. Benchmarked up to 68% fewer tokens vs native tools.
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    Apache 2.0
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    Local-first code indexer that provides deep code understanding for Claude and other LLMs with symbol/text search across 48+ languages, semantic search capabilities, and real-time index updates through the Model Context Protocol.
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    AI-powered code review tool that detects AI-generated code defects invisible to traditional linters — hallucinated packages, deprecated APIs, cross-file contradictions, hidden security anti-patterns, and over-engineering. Works as a standalone CLI, GitHub Action, or MCP server. Supports TypeScript, Python, Java, Go, and Kotlin. Free for individuals, no API key required.
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    Enables comprehensive GitHub PR reviews through Cursor's AI by fetching PR diffs, running static analysis tools (ESLint, Prettier, TypeScript, Semgrep), executing tests, and generating detailed code review reports with inline comments.
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    An MCP server that implements Claude Code-like functionality, allowing the AI to analyze codebases, modify files, execute commands, and manage projects through direct file system interactions.
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    A Python-based MCP server that provides coordinate conversion between latitude/longitude and UTM/TWD97, along with various civil engineering calculation tools for LLM and AI application integration.
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    An MCP server that provides tools for JSON validation, diffing, and transformation operations such as flattening and renaming. It also enables data format conversion between JSON, CSV, and YAML to streamline data processing for AI agents.
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    Universal MCP server for executing TypeScript and Python code with progressive disclosure, reducing token usage by 98% by enabling on-demand access to all other MCP tools through code execution rather than loading tool definitions directly.
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    An adaptation of the MCP Sequential Thinking Server designed to guide tool usage in problem-solving. This server helps break down complex problems into manageable steps and provides recommendations for which MCP tools would be most effective at each stage.
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    Provides access to OpenAI's advanced models (including o3) with integrated web search, Python code interpreter, and combined analysis capabilities. Enables users to perform web searches, execute code in sandboxed environments, and combine search with analysis through natural language.
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    A server that provides advanced mathematical and financial calculation capabilities for AI code assistants, enabling them to perform complex calculations like symbolic calculus, numerical methods, and financial analysis without implementing algorithms directly.
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    Enables AI-assisted code review with bias mitigation strategies through cross-model evaluation and bias-aware prompting. Detects AI-generated code from commit authors and provides structured reviews with security, performance, and maintainability analysis.
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    MIT