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Model Context Protocol

Anthropic
open source / Overall score: 5.0(leading)

Model Context Protocol is an open standard for connecting AI agents to external tools and data sources, defining how an agent discovers, authenticates with and invokes a tool over JSON-RPC. Anthropic announced it in November 2024 and donated it to the Linux Foundation's Agentic AI Foundation in December 2025. The specification, schema and documentation live in one repository, with official SDKs in separate repositories for languages including Python, TypeScript, C#, Java, Go, Rust and Ruby.

The protocol has no package of its own, so the reference SDK packages its adoption is read from are declared here as well as on mcp-python-sdk and mcp-typescript-sdk, which score the SDKs themselves.

Openness

5 high confidence
5.0
source
public(spec schema and docs in one repo plus reference SDKs in separate public repos)
license
Apache-2.0(OSI, new code/spec)+MIT(OSI, legacy contributions)
docs
CC-BY-4.0(documentation other than the specifications
core features withheld
no — spec schema and docs ship in the one LF/AAIF-governed repo and every reference SDK is a public modelcontextprotocol repo - there is no vendor tier to withhold anything for

Model Context Protocol's specification, schema and documentation live in one public repository, and every reference SDK is a separate public repository under the same project. No vendor sells an edition of the protocol beside them. The license splits by contribution: new code and specification contributions are under Apache-2.0 and earlier contributions stay under MIT, both OSI-approved.

Adoption

5 high confidence
5.0

OpenAI uses Model Context Protocol across ChatGPT, its Agents SDK and the Responses API, Google DeepMind supports it in Gemini, and Microsoft's Semantic Kernel and Azure OpenAI integrate with it. The protocol has no package of its own, so adoption is measured by downloads of its two reference SDKs, `mcp` on PyPI and the TypeScript SDK's `@modelcontextprotocol/sdk` on npm, each also listed on the map as its own entry.

Capability

not assessed

MCP ships a specification, schema and documentation, and the repository publishes no benchmark, leaderboard or performance figure, so there is nothing to score for capability. Implementation breadth already shows up in the SDK downloads counted under adoption, and the Agent2Agent and Agent Client protocols are left unscored for the same reason.

  • https://api.github.com/repos/modelcontextprotocol/modelcontextprotocol recorded 2026-08-14

    Repo metadata - description "Specification and documentation for the Model Context Protocol", topics docs / mcp / specification / standard, 8,950 stars, homepage modelcontextprotocol.io. What the project ships is a specification and its schema, and no benchmark result, leaderboard entry or performance figure is published for it.

  • https://modelcontextprotocol.io/docs/getting-started/intro recorded 2026-09-29

    The docs introduction calls it "an open-source standard for connecting AI applications to external systems" and describes what it enables, with no benchmark, leaderboard or performance figure. Searched the body for benchmark and leaderboard: none.

  • https://raw.githubusercontent.com/modelcontextprotocol/modelcontextprotocol/main/README.md recorded 2026-09-29

    The spec repository README states it contains the "MCP specification", the "MCP protocol schema" and "Official MCP documentation", with the schema "defined in TypeScript" first and made available as JSON Schema. Searched the body for benchmark, leaderboard, score and performance: none, so the repository publishes no benchmark result.

Verified 2026-09-28