Awesome MCP - Model Context Protocol
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
January 9, 2026 at 02:10:40 AM UTC
Theorem
Papers (45)
- Agentic Semantic Control for Autonomous Wireless Space Networks: Extending Space-O-RAN with MCP-Driven Distributed Intelligence
- Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol Ecosystem
- ETDI: Mitigating Tool Squatting and Rug Pull Attacks in Model Context Protocol (MCP) by using OAuth-Enhanced Tool Definitions and Policy-Based Access Control
- Gaming Tool Preferences in Agentic LLMs
- Enterprise-Grade Security for the Model Context Protocol (MCP): Frameworks and Mitigation Strategies
- Securing GenAI Multi-Agent Systems Against Tool Squatting: A Zero Trust Registry-Based Approach
- MCP Bridge: A Lightweight, LLM-Agnostic RESTful Proxy for Model Context Protocol Servers
- MCP Safety Audit: LLMs with the Model Context Protocol Allow Major Security Exploits
- Beyond Formal Semantics for Capabilities and Skills: Model Context Protocol in Manufacturing
- Mind the Metrics: Patterns for Telemetry-Aware In-IDE AI Application Development using the Model Context Protocol (MCP)
- We Should Identify and Mitigate Third-Party Safety Risks in MCP-Powered Agent Systems
- Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Servers
- Gradientsys: A Multi-Agent LLM Scheduler with ReAct Orchestration
- MemTool: Optimizing Short-Term Memory Management for Dynamic Tool Calling in LLM Agent Multi-Turn Conversations
- Magentic-UI: Towards Human-in-the-loop Agentic Systems
- MCP2OSC: Parametric Control by Natural Language
- Help or Hurdle? Rethinking Model Context Protocol-Augmented Large Language Models
- Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol (MCP) Ecosystem
- AniME: Adaptive Multi-Agent Planning for Long Animation Generation
- MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers
- Towards Agentic OS: An LLM Agent Framework for Linux Schedulers
- EHR-MCP: Real-world Evaluation of Clinical Information Retrieval by Large Language Models via Model Context Protocol
- XARP Tools: An Extended Reality Platform for Humans and AI Agents
- Tool Preferences in Agentic LLMs are Unreliable
- Dynamic ReAct: Scalable Tool Selection for Large-Scale MCP Environments
- Model Context Protocol for Vision Systems: Audit, Security, and Protocol Extensions
- IoT-MCP: Bridging LLMs and IoT Systems Through Model Context Protocol
- Agentic-AI Healthcare: Multilingual, Privacy-First Framework with MCP Agents
- LLM\times\timesMapReduce-V3: Enabling Interactive In-Depth Survey Generation through a MCP-Driven Hierarchically Modular Agent System
- NetMCP: Network-Aware Model Context Protocol Platform for LLM Capability Extension
- Securing AI Agent Execution
- ORCHID: Orchestrated Retrieval-Augmented Classification with Human-in-the-Loop Intelligent Decision-Making for High-Risk Property
- TEM Agent: enhancing transmission electron microscopy (TEM) with modern AI tools
- Hiding in the AI Traffic: Abusing MCP for LLM-Powered Agentic Red Teaming
- Securing the Model Context Protocol (MCP): Risks, Controls, and Governance
- MCP vs RAG vs NLWeb vs HTML: A Comparison of the Effectiveness and Efficiency of Different Agent Interfaces to the Web (Technical Report)
- PaperDebugger: A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing
- Leveraging Large Language Models to Bridge On-chain and Off-chain Transparency in Stablecoins
- LeechHijack: Covert Computational Resource Exploitation in Intelligent Agent Systems
- Benchmark for Planning and Control with Large Language Model Agents: Blocksworld with Model Context Protocol
- AgentBay: A Hybrid Interaction Sandbox for Seamless Human-AI Intervention in Agentic Systems
- RoboNeuron: A Modular Framework Linking Foundation Models and ROS for Embodied AI
- MobileWorld: Benchmarking Autonomous Mobile Agents in Agent-User Interactive and MCP-Augmented Environments
- Agentic AI for Autonomous Defense in Software Supply Chain Security: Beyond Provenance to Vulnerability Mitigation
- Enterprise Identity Integration for AI-Assisted Developer Services: Architecture, Implementation, and Case Study
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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
- Fork the repository.
- Create a new branch for your changes.
- Make your changes and commit them with a clear message.
- Push your changes to your forked repository.
- 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.