Draft:Model Context Protocol Source: en.wikipedia.org/wiki/Draft:Model_Context_Protocol

Submission declined on 23 April 2025 by Brandon (talk). Thank you for your submission, but the subject of this article already exists in Wikipedia. You can find it and improve it at Model Context Protocol instead. If you would like to continue working on the submission, click on the "Edit" tab at the top of the window. If you have not resolved the issues listed above, your draft will be declined again and potentially deleted. If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors. Please do not remove reviewer comments or this notice until the submission is accepted. Where to get help If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews. If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed. How to improve a draft Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia. Help:Wikitext – how to use the markup Help:Referencing for beginners – how to include references Wikipedia:Article development – how to develop your article Wikipedia:Writing better articles – how to improve your article Wikipedia:Verifiability – make sure your article includes reliable third-party sources You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Add tags to your draft Editor resources Easy tools: Citation bot (help) | Advanced: Fix bare URLs Declined by Brandon 1 month ago. Last edited by Brandon 1 month ago. Reviewer: Inform author. Resubmit Please note that if the issues are not fixed, the draft will be declined again.

Submission declined on 28 March 2025 by Caleb Stanford (talk). Neologisms are not considered suitable for Wikipedia unless they receive substantial use and press coverage; this requires strong evidence in independent, reliable, published sources. Links to sites specifically intended to promote the neologism itself do not establish its notability. Declined by Caleb Stanford 2 months ago.

Submission declined on 2 January 2025 by Beachweak (talk). This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are: in-depth (not just passing mentions about the subject) reliable secondary independent of the subject Make sure you add references that meet these criteria before resubmitting. Learn about mistakes to avoid when addressing this issue. If no additional references exist, the subject is not suitable for Wikipedia. Declined by Beachweak 5 months ago.

• Comment: Fails WP:TOOSOON IMO. I don't doubt that this is an important protocol or may be at some point in the future, but the current sources are mostly primary and don't demonstrate that the protocol is considered of general importance beyond Anthropic and a few notes on Google Scholar. While I don't think it yet merits an article, could be worth a mention at Prompt engineering or similar. Caleb Stanford (talk) 00:24, 28 March 2025 (UTC)

• Comment: GitHub and primary sources about the software are unreliable, as they are made up of user-generated content. Please find other sources to establish notability and expand the article in order to get it published. Beachweak (talk) 02:09, 2 January 2025 (UTC)

The Model Context Protocol (MCP) is an open-source framework introduced by Anthropic to standardize the way artificial intelligence (AI) models like large language models (LLMs) integrate and share data from diverse sources.^[1] Similar to how USB-C standardizes connections between devices and peripherals, MCP provides a universal interface for AI models to seamlessly integrate and interact with external data sources and tools.^[2]

The protocol was announced in November 2024^[3] as an open-source^[4] standard for connecting AI assistants to systems where data lives, including content repositories, business tools, and development environments.^[5] It addresses the challenge of information silos and legacy systems that constrain even the most sophisticated AI models.^[5]

MCP defines a set of specifications for:

• Data ingestion and transformation
• Contextual metadata tagging
• Model interoperability across platforms
• Secure, two-way connections between data sources and AI-powered tools^[5]

The protocol enables developers to either expose their data through MCP servers or build AI applications (MCP clients) that connect to these servers.^[5] Key components include:

• Protocol specification and SDKs
• Local MCP server support in Claude Desktop apps
• Open-source repository of MCP servers^[5]

Early adopters like Block and Apollo have integrated MCP into their systems, while development tools companies including Replit, Codeium, and Sourcegraph are working with MCP to enhance their platforms.^[5] These integrations enable AI agents to better retrieve relevant information and produce more nuanced outputs with fewer attempts.^[5]

Dhanji R. Prasanna, Chief Technology Officer at Block, stated: "Open technologies like the Model Context Protocol are the bridges that connect AI to real-world applications, ensuring innovation is accessible, transparent, and rooted in collaboration."^[5]

In March 2025, OpenAI officially adopted the Model Context Protocol (MCP), following a decision to integrate the standard across its products, including the ChatGPT desktop app. OpenAI CEO Sam Altman announced the move, emphasizing that MCP support would be available in the OpenAI Agents SDK, with future support planned for the ChatGPT desktop app and the Responses API. This integration allows developers to connect their MCP servers to AI agents, simplifying the process of providing tools and context to large language models (LLMs).

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.^[6][7]

By adopting MCP, OpenAI joins other organizations such as Block, Inc., Replit, Codeium, and Sourcegraph in incorporating the protocol into their platforms. This wide adoption highlights MCP's potential to become a universal standard for AI system connectivity and interoperability.^[8][9] MCP can be integrated with Microsoft Semantic Kernel,^[10] and Azure OpenAI.^[11] MCP servers can be deployed to Cloudflare.^[12]

Anthropic has provided pre-built MCP servers for popular enterprise systems including:

• Google Drive
• Slack
• GitHub
• Git
• Postgres
• Puppeteer^[5]

The open-source repository of MCP server implementations is available on GitHub, providing developers with examples and foundations for building custom integrations.^[13]

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.^[5]

• Application programming interface
• Machine learning
• AI governance

• Andersen, Jason (April 1, 2025). "Open-Sourcing And Accelerating Agent Adoption With MCP". Forbes.
• Edwards, Benj (April 1, 2025). "MCP: The new "USB-C for AI" that's bringing fierce rivals together". Ars Technica.
• Jackson, Fiona (March 28, 2025). "OpenAI Agents Now Support Rival Anthropic's Protocol, Making Data Access 'Simpler, More Reliable'". TechRepublic.
• Janakiram MSV (November 30, 2024). "Why Anthropic's Model Context Protocol Is A Big Step In The Evolution Of AI Agents". Forbes.
• Greiner, Lynn (November 26, 2024). "Anthropic introduces the Model Context Protocol". InfoWorld.
• Wiggers, Kyle (November 25, 2024). "Anthropic proposes a new way to connect data to AI chatbots". TechCrunch.
• Dickson, Ben (March 31, 2025). "What is Model Context Protocol (MCP)?". TechTalks.
• Masson, Colin (March 25, 2025). "Context Is the Missing Link: The Emergence of the Model Context Protocol in Industrial AI". ARC Advisory Group.
• Bastian, Matthias (November 25, 2024). "Anthropic's new open protocol lets AI systems tap into any data source". The Decoder.
• Jimin Kim; Anita Lewis; Justin Lewis; Laith Al-Saadoon; Paul Vincent; Pranjali Bhandari (April 1, 2025). "Introducing AWS MCP Servers for code assistants (Part 1)". Amazon AWS.
• Desai, Zankar (March 19, 2025). "Introducing Model Context Protocol (MCP) in Copilot Studio: Simplified Integration with AI Apps and Agents". Microsoft Copilot Studio Blog, Microsoft.

• "Model Context Protocol". Github.
• "Model Context Protocol: Introduction". modelcontextprotocol.io. Retrieved April 2, 2025.

Category:Artificial intelligence Category:Open standards