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MCP server · AI

Awesome MCP

A carefully curated collection of high-quality tools, libraries, research papers, projects, and tutorials centered around Model Context Protocol (MCP) — a novel paradigm designed to enable modular, adaptive coordination between large language models (LLMs) and external tools or data contexts.

Unclaimed Custom license mcpmodel-context-protocol
70Good

Scored 14 hours ago · breakdown

About Awesome MCP

Awesome MCP is an MCP server published by AI-in-Transportation-Lab in the AI category: a carefully curated collection of high-quality tools, libraries, research papers, projects, and tutorials centered around Model Context Protocol (MCP) — a novel paradigm designed to enable modular, adaptive coordination between large language models (LLMs) and external tools or data contexts.

The repository has 11 stars and 27 forks, with the last commit yesterday. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/AI-in-Transportation-Lab/awesome-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository 15 hours ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

Awesome MCP - Model Context Protocol

Awesome License GitHub Contributors GitHub Last Commit GitHub Stars GitHub Forks

A carefully curated collection of high-quality tools, libraries, research papers, projects, and tutorials centered around Model Context Protocol (MCP) — a novel paradigm designed to enable modular, adaptive coordination between large language models (LLMs) and external tools or data contexts. This repository serves as a comprehensive, well-organized knowledge hub for researchers and developers exploring the next frontier of interactive, context-aware AI systems.

The MCP framework facilitates fine-grained orchestration of model behavior through structured, tool-integrated communication protocols. It supports advanced workflows like adaptive reasoning, multi-tool routing, contextual memory access, and iterative refinement. By treating models not as static endpoints but as participants in a dynamic co-mining or co-creation loop, MCP pushes the boundaries of what intelligent systems can achieve.

To keep the community up-to-date with the latest developments, this repository is continuously enriched with newly published MCP-related papers, real-world use cases, and open-source implementations. From LangGraph-based architectures to custom tool routers and model-control interfaces, the collection aims to highlight both foundational ideas and emerging best practices.

[!NOTE] 📢 Announcement: Our paper is now available on arXiv!
Title: Model Context Protocols in Adaptive Transport Systems: A Survey
If you find this paper interesting, please consider citing our work. Thank you for your support!

@article{chhetri2025model,
  title={Model Context Protocols in Adaptive Transport Systems: A Survey},
  author={Chhetri, Gaurab and Somvanshi, Shriyank and Islam, Md Monzurul and Brotee, Shamyo and Mimi, Mahmuda Sultana and Koirala, Dipti and Pandey, Biplov and Das, Subasish},
  journal={arXiv preprint arXiv:2508.19239},
  year={2025}
}

Whether you are building AI agents, researching model-tool alignment, or experimenting with novel retrieval-augmented generation pipelines, this resource offers a centralized, evolving platform to explore the powerful and expanding universe of MCP-enabled systems.

Last Updated

October 17, 2026 at 03:55:30 AM UTC

Theorem

Papers (169)

Library

  • WritBase - MCP-native task management for AI agent fleets. Multi-agent permissions, full provenance, inter-agent task delegation, and A2A protocol alignment.
  • Roundtable - Multi-model AI brainstorming MCP server — consult a council of AI models that debate your question, then a moderator synthesizes the best answer. 13 tools including consult_council, review_code, debug_issue, design_architecture, plan_implementation, and assess_tradeoffs. Remote endpoint: https://mcp.roundtable.now/mcp.
  • operant-mcp - Security testing MCP server with 51 tools for penetration testing, network forensics, memory analysis, and vulnerability assessment.

Tutorial

Written Tutorials

Video Tutorials

Contributing

We welcome contributions to this repository! If you have a resource that you believe should be included, please submit a pull request or open an issue. Contributions can include:

  • New libraries or tools related to MCP.
  • Tutorials or guides that help users understand and implement MCP.
  • Research papers that advance the field of MCP.
  • Any other resources that you find valuable for the community

How to Contribute

  1. Fork the repository.
  2. Create a new branch for your changes.
  3. Make your changes and commit them with a clear message.
  4. Push your changes to your forked repository.
  5. Submit a pull request to the main repository.

Before contributing, take a look at the existing resources to avoid duplicates.

License

This repository is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). You are free to share and adapt the material, provided you give appropriate credit, link to the license, and indicate if changes were made.

Star History

Star History Chart

README fetched from the repository 15 hours ago. The original is authoritative.

Questions

About Awesome MCP

How do I install Awesome MCP?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Awesome MCP safe to use with an AI agent?

Its trust score is 70 out of 100 (good). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Awesome MCP still maintained?

Yes — the last commit was yesterday. The repository has 11 stars and 27 forks and 27 open issues.