Model Context Protocol

Model Context Protocol
Developed byAnthropic
IntroducedNovember 25, 2024 (2024-11-25)
Websitemodelcontextprotocol.io

The Model Context Protocol (MCP) is an open standard, open-source framework introduced by Anthropic to standardize the way artificial intelligence (AI) models like large language models (LLMs) integrate and share data with external tools, systems, and data sources.[1] Technology writers have dubbed MCP “the USB-C of AI apps”,[2] underscoring its goal of serving as a universal connector between language-model agents and external software. Designed to standardize context exchange between AI assistants and software environments, MCP provides a model-agnostic universal interface for reading files, executing functions, and handling contextual prompts.[3] It was officially announced and open-sourced by Anthropic in November 2024, with subsequent adoption by major AI providers including OpenAI and Google DeepMind.[4][5]

Background

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The protocol was announced in November 2024 as an open standard[6] for connecting AI assistants to data systems such as content repositories, business management tools, and development environments.[7] It addresses the challenge of information silos and legacy systems that constrain even the most sophisticated AI models.[7]

Anthropic introduced MCP to address the growing complexity of integrating LLMs with third-party systems. Before MCP, developers often had to build custom connectors for each data source or tool, resulting in what Anthropic described as an "N×M" data integration problem.[7]

Earlier stop-gap approaches - such as OpenAI’s 2023 “function-calling” API and the ChatGPT plug-in framework - solved similar problems but required vendor-specific connectors.[2] MCP’s authors note that the protocol deliberately re-uses the message-flow ideas of the Language Server Protocol (LSP) and is transported over JSON-RPC 2.0.[8]

MCP was designed as a response to this challenge, offering a universal protocol for interfacing any AI assistant with any structured tool or data layer. The protocol was released with software development kits (SDK) in multiple programming languages, including Python, TypeScript, Java, and C#.[9]

Features

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MCP defines a set of specifications for:

The protocol enables developers to either expose their data through MCP servers or build AI applications (MCP clients) that connect to these servers.[7] Key components include:

  • Protocol specification and SDKs
  • Local MCP server support in Claude Desktop apps
  • Open-source repository of MCP servers[7]

Applications

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MCP has been applied across a range of use cases in software development, business process automation, and natural language automation:

Implementation

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Anthropic maintains an open-source repository of reference MCP server implementations for popular enterprise systems including Google Drive, Slack, GitHub, Git, Postgres, Puppeteer and Stripe.[12]

Developers can create custom MCP servers to connect proprietary systems or specialized data sources to AI models. These custom implementations enable:

  • Real-time access to private databases and internal tools
  • Secure integration with sensitive business systems
  • Context-aware AI responses based on organizational knowledge
  • Automated workflows across multiple business applications
  • Custom data processing pipelines for AI consumption

The protocol's open standard allows organizations to build tailored connections while maintaining compatibility with the broader MCP ecosystem. AI models can then leverage these custom connections to provide domain specific assistance while respecting data access permissions.[7]

https://zontroy.com/mcp-tools== Adoption == In March 2025, OpenAI officially adopted the MCP, following a decision to integrate the standard across its products, including the ChatGPT desktop app, OpenAI's Agents SDK, and the Responses API. Altman described the adoption of MCP as a step toward standardizing AI tool connectivity. Prior to OpenAI's adoption, the potential benefits of MCP had been discussed extensively within the developer community, particularly for simplifying development in multi-model environments.[4][3]

By adopting MCP, OpenAI joins other organizations such as Block, Replit, and Sourcegraph in incorporating the protocol into their platforms. This wide adoption highlights MCP's potential to become a universal open standard for AI system connectivity and interoperability.[4] The rapid growth and broad community adoption of MCP are demonstrated by Glama's publicly available MCP server directory, which lists over 5,000 active MCP servers as of May 2025.[13] MCP can be integrated with Microsoft Semantic Kernel,[14] and Azure OpenAI.[15] MCP servers can be deployed to Cloudflare.[16]

Demis Hassabis, CEO of Google DeepMind, confirmed in April 2025 MCP support in the upcoming Gemini models and related infrastructure, describing the protocol as "rapidly becoming an open standard for the AI agentic era".[5]

Many MCP servers have since been added, allowing integration of LLMs with diverse applications.[17]

Reception

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The Verge reported that MCP addresses a growing demand for AI agents that are contextually aware and capable of securely pulling from diverse sources.[6] The protocol's rapid uptake by OpenAI, Google DeepMind, and toolmakers like Zed and Sourcegraph suggests growing consensus around its utility.[4][18]

In April 2025, security researchers released analysis that there are multiple outstanding security issues with MCP, including prompt injection,[19] tool permissions where combining tools can exfiltrate files,[20] and lookalike tools can silently replace trusted ones.[21]

It has been likened to OpenAPI, a similar specification that aims to describe APIs.[22][23]

See also

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  • AI governance – Guidelines and laws to regulate AI
  • Application programming interface – Connection between computers or programs
  • LangChain – Language model application development framework
  • Machine learning – Study of algorithms that improve automatically through experience
  • Software agent – Computer program acting for a user

Notes

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  1. ^ David, Emilia (November 25, 2024). "Anthropic releases Model Context Protocol to standardize AI-data integration". VentureBeat. Retrieved 2025-05-12.
  2. ^ a b Edwards, Benj (1 April 2025). "MCP: The new "USB-C for AI" that's bringing fierce rivals together". Ars Technica. Retrieved 2025-05-24.
  3. ^ a b Kumar, Vinay (March 26, 2025). "The open source Model Context Protocol was just updated — here's why it's a big deal". VentureBeat. Retrieved 2025-05-12.
  4. ^ a b c d Wiggers, Kyle (March 25, 2025). "OpenAI adopts rival Anthropic's standard for connecting AI models to data". TechCrunch.
  5. ^ a b Wiggers, Kyle (April 9, 2025). "Google to embrace Anthropic's standard for connecting AI models to data". TechCrunch. Retrieved 2025-05-12.
  6. ^ a b c Roth, Emma (November 25, 2024). "Anthropic launches tool to connect AI systems directly to datasets". The Verge.
  7. ^ a b c d e f g h "Introducing the Model Context Protocol". Anthropic. November 25, 2024. Retrieved 2025-05-12.[non-primary source needed]
  8. ^ "Model Context Protocol Specification (§Base Protocol)". modelcontextprotocol.io. 26 March 2025. Retrieved 2025-05-24.
  9. ^ a b "Agents and tools: Model Context Protocol (MCP)". docs.anthropic.com.[failed verification]
  10. ^ "Wix just opened the door to quicker and easier coding with new AI tool". TechRadar Pro. March 27, 2025. Retrieved 2025-05-22.
  11. ^ "Wix Unveils the Wix Model Context Protocol Server for AI-Driven Web App Development". Enterprise AI World. March 27, 2024. Retrieved 2025-05-22.
  12. ^ "Model Context Protocol Servers". GitHub. Retrieved 2025-05-12.[non-primary source needed]
  13. ^ "Glama MCP Server Directory". Retrieved 2025-05-21.
  14. ^ Wallace, Mark (March 5, 2025). "Integrating Model Context Protocol Tools with Semantic Kernel: A Step-by-Step Guide". Semantic Kernel Dev Blog, Microsoft. Retrieved 2025-05-12.
  15. ^ mrajguru (March 16, 2025). "Model Context Protocol (MCP): Integrating Azure OpenAI for Enhanced Tool Integration and Prompting". AI - Azure AI services Blog, Microsoft. Retrieved 2025-05-12.
  16. ^ Brendan Irvine-Broque; Dina Kozlov; Glen Maddern (March 25, 2025). "Build and deploy Remote Model Context Protocol (MCP) servers to Cloudflare". Cloudflare. Retrieved 2025-05-12.
  17. ^ Awan, Abid Ali. "10 Awesome MCP Servers". KDnuggets. Retrieved 2025-05-12.
  18. ^ Sha, Arjun (April 14, 2025). "What is Model Context Protocol (MCP) Explained". Beebom.com.
  19. ^ Lakshmanan, Ravie (30 April 2025). "Researchers Demonstrate How MCP Prompt Injection Can Be Used for Both Attack and Defense". thehackernews.com.
  20. ^ Beurer-Kellner, Luca; Fischer, Marc (1 April 2025). "MCP Security Notification: Tool Poisoning Attacks". InvariantLabs.
  21. ^ Schulz, Kasimir; Martin, Jason; Kan, Marcus; Yeung, Kenneth; McCauley, Conor; Ring, Leo (10 April 2025). "MCP: Model Context Pitfalls in an Agentic World". hiddenlayer.com.
  22. ^ MacManus, Richard (13 March 2025). "MCP: The Missing Link Between AI Agents and APIs". The New Stack. Retrieved 29 May 2025.
  23. ^ Fanelli, Alessio. "Why MCP Won". www.latent.space. Retrieved 29 May 2025.

References

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