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"A tool for detecting code duplication in programming" matching MCP servers:

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    CodeGuard MCP is a real-time AI code security scanning tool used to detect vulnerabilities, keys, and compliance issues in AI-generated code, and is suitable for code security reviews in development environments
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    Apache 2.0
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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 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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    An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.
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    MIT
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    Fast pre-commit dependency gate for AI-assisted code changes. Answers "is this safe to commit?" with a PASS/WARN/BLOCK verdict in seconds, so you can catch risky blast radius before a bad commit, not after it. No database, no heavy setup.
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    MIT
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    Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.
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    MIT
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    Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.
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    Apache 2.0
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    Strict AI code reviewer powered by Groq. Finds bugs, vulnerabilities and security issues in your code. Supports analyze, compare versions, explain code, generate tests, and HTML reports.
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    MIT
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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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    MIT
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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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    MIT
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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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