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    . A good description should be concise and describe what the server enables users to do, e.g. * Enables to interact with WordPress sites...' Then a huge block? Actually the user message includes the README content inside tags, then after the readme, there is a large block of text starting with '{
    6,998 npm
    MIT
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    Enables cross-repository code search over a local mirror of a self-hosted Gitea or Forgejo instance, covering file contents, file paths, and commit messages across all repositories and branches. It also lets users read a single file from the mirror and list mirrored repositories, all without network access during search or read.
    123 npm
    7
    Apache 2.0
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    A secure and scalable Git MCP server giving AI agents powerful version control for local and (soon) serverless environments.
    130 npm
    Apache 2.0
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    A deterministic MCP server that reimplements ai-git-fish workflows (aicommit, aibranch, aipr) with Leantime integration, enabling Claude Code and Codex to perform git operations and manage tickets without an internal LLM.
    9
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    RCP-1 is an enterprise-ready MCP server that connects AI assistants to SAP ABAP systems via the ADT REST API, with built-in security, access controls, and deployment options for BTP or on-premise.
    8
    MIT
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    Coordination protocol for parallel coding agents, built above Git. The MCP server exposes the full 17-tool lifecycle over stdio: register agents, publish intents with semantic scopes and declared operations, claim work, check for conflicts before code is written, publish ChangeSets, run trusted named verification checks, and record accepted work. Deterministic rules raise findings when two agents'
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    529
    Apache 2.0
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    Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.
    2
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    MIT
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    MCP server for GitHub code retrieval and reuse, using SQLite+FTS5 indexing and search history to enable search-first, requirements-refined code search from GitHub repositories.
    9
    2
    MIT
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    Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.
    3
    480 npm
    1
    MIT
  • A
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    Git-native long-term memory for AI agents: your markdown files are the source of truth, the search index is a disposable projection rebuilt from git, and every memory the agent writes is a reviewable git commit. Served over one OAuth-secured MCP endpoint with hybrid lexical+semantic recall and a gated, git-first commit_note write tool.
    7
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    AGPL 3.0
  • F
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    Enables natural language code search across multiple local Git repositories, allowing users to register projects, search for code, and explore file structures through Claude.
    6
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    Enables auditing web pages for WCAG violations, applying deterministic fixes and PRs, all through MCP clients like Claude Desktop.
    7
    MIT
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    Enables AI agents to analyze public GitHub repositories directly through tools for repo health scoring, recent commit summaries, good first issue discovery, and semantic Q&A over docs and issues.
    4
    27 npm
    1
    MIT
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    MCP server that detects semantic (non-textual) merge conflicts between Git branches using AST-level analysis. Catches incompatible changes that Git merges cleanly — signature changes, removed exports, parameter changes, interface breaks, and cross-file dependency conflicts.
    4
    20 npm
    MIT
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    Provides intelligent file system operations with advanced features including code analysis and modification across multiple languages, version control (Git/GitHub), file compression, encryption, semantic search, batch operations, and secure shell command execution.
    1
    6
    MIT
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    Enables version-controlled golden dataset management and semantic evaluation for RAG/LLM pipelines using TF-IDF cosine similarity, without requiring an LLM API key.
    9
    MIT