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    Exposes structured Microsoft Dynamics 365 Business Central source code (versions 23-29, 47 localizations) to AI agents via MCP, enabling fast lookups, searches, and code analysis.
    14
    27 npm
    MIT
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    An MCP server that bridges ChatGPT Web Pro to local tools, enabling file read/write, shell command execution, git operations, and search within a specified project directory.
    32
    MIT
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    An MCP execution layer that lets capable AI models safely control a developer workstation for file edits, terminal and process execution, Git operations, language-server analysis, browser and Windows UI automation, media processing, job/resource control, and checkpointing. It also coordinates durable single- or multi-agent tasks across providers with leases, dependency graphs, evidence logs, repair loops, and separate verification gates.
    128
    1
    ISC
  • A
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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
    124 npm
    1
    MIT
  • A
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    Enables AI agents to find public GitHub repositories matching plain-language project descriptions, filter low-quality results by ranking, and fetch a repository's README.
    1
    Creative Commons Attribution Non Commercial Share Alike 4.0 International
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    quality
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    Enables LLMs to perform advanced GitHub code searches with intelligent filtering and content retrieval using Playwright automation, optimized for DeepSeek integration.
    4
    4
    MIT
  • A
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    maintenance
    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.
    116 npm
    8
    Apache 2.0
  • A
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    quality
    A
    maintenance
    Enables agents to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited progress events with matching Git commits through short-lived scoped credentials.
    MIT
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    maintenance
    Enables Codex agents to read a project's kickoff card, acceptance criteria, handoff package, progress, Git trail and next step, then append validated, audited, idempotent progress events that become matching project-record Git commits. Access is scoped to one workspace and project through short-lived, revocable, hash-stored credentials that cannot touch members, keys, deletion, publication or deployment.
    MIT
  • A
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    maintenance
    It lets AI coding clients read a project’s kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, then append a validated, audited, idempotent progress event with a matching project-record Git commit.
    MIT
  • F
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    quality
    A
    maintenance
    Enables AI agents and humans to read a project's kickoff card, acceptance criteria, handoff package, progress, Git trail, and next step, then append audited, idempotent progress events that are committed to the project's Git record. Access is scoped per project through short-lived, revocable credentials, keeping high-risk actions outside the tool surface for human approval.
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  • F
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    maintenance
    Enables Codex agents to read a project's context — kickoff card, acceptance criteria, handoff package, progress, Git trail, and next step — over MCP, and to append one validated, audited, idempotent progress event that is committed to a Git-backed project record using scoped, short-lived credentials.
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  • F
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    quality
    A
    maintenance
    It reads a project's kickoff card, acceptance criteria, AGENTS rules, progress, Git trail, and handoff package, and appends validated, audited progress events tied to project-record Git commits. This gives Codex agents scoped, credential-bound access to resumable project context and safe handoffs.
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  • F
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    quality
    A
    maintenance
    Enables AI agents to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, then append validated, audited, idempotent progress events that are recorded as a matching Git commit. This keeps project truth in Git so work stays visible, resumable, and safely handable between humans and agents through scoped, short-lived credentials.
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    Enables reasoning agents to turn PRDs into production-ready applications by discovering and reusing existing features, UI components, database models, and templates, then planning, scaffolding, validating, and preparing Git changes for review.
    29
    MIT
  • A
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    maintenance
    Enables AI coding assistants to search and retrieve code from self-hosted Git repositories using semantic and lexical search with optional reranking, while keeping repository data under the operator's control.
    MIT
  • A
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    Not graded
    quality
    B
    maintenance
    Enables users to manage self-hosted Git repositories from ChatGPT and compatible Codex clients via OAuth-secured connections, with independent browser approval for write actions. Supports repository, file, branch, issue, pull request, release, and workflow operations while excluding administrative tools.
    Apache 2.0
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    A
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    Enables AI agents to perform unified web searches, GitHub, and GitLab searches with caching, reranking, and fallback across multiple providers.
    4
    176 npm
    20
    MIT
  • A
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    quality
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    A Model Context Protocol server that provides tools for searching private GitHub repositories, enabling access to repository files, commit history, and issues with automatic handling of rate limiting and error handling.
    4
    23 npm
    10
    MIT
  • A
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    A Python-based Model Context Protocol server that provides 87 tools for comprehensive interaction with the GitHub API. It enables AI agents to manage repositories, issues, pull requests, workflows, and projects through automated commands.
    87
    MIT