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    Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.
    1
    19
    MIT
  • A
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    Enables efficient analysis of large codebases using Claude Code and Kimi K2.5 through the Model Context Protocol, with session caching and parallel processing to reduce costs and time.
    4
    7
    72
    1
    MIT
  • A
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    Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.
    6
    15
    ISC
  • A
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    Enables AI coding assistants to interact with OpenAI's Codex AI through the official CLI. Provides direct integration for code analysis, file review, and batch processing with zero API costs.
    3
    113
    MIT
  • A
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    MCP server that brings Octopus AI code review into editors, allowing review of code changes and asking questions about your codebase. Integrates with Cursor, Claude, or any MCP client via natural language.
    3
    MIT
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    Enables AI assistants to audit Solidity smart contracts for security vulnerabilities, fetch verified source code from block explorers, decode calldata, and estimate gas costs across major EVM networks.
    4
    MIT
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    Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.
    9
    19
    4
    MIT
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    An MCP server for gitingest. It allows MCP clients like Claude Desktop, Cursor, Cline etc to quickly extract information about Github repositories including repository summaries, project directory structure, file contents, etc
    3
    136
    MIT
  • F
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    Provides tools for mapping and analyzing GitHub repositories. It allows users to set a GitHub Personal Access Token and retrieve detailed information about a specified repository, including its structure and summary statistics.
    2
    25
  • A
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    Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.
    4
    1
    MIT
  • A
    license
    Not graded
    quality
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    maintenance
    Exposes Lachesis's code navigation tools over MCP, letting LLM agents ask precise compiler-level questions about dataflow, taint, callers, and guards in source code.
    3
    AGPL 3.0
  • A
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    quality
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    maintenance
    A local, read-only MCP server that provides AI coding agents with structural evidence about a repository, including dependency analysis and impact assessment, while naming the boundary of every answer without any LLM calls.
    Apache 2.0