Model Context Protocol

What Model Context Protocol does

Model Context Protocol (MCP) is an open-source protocol standard that provides a standardized connection layer between AI applications and external systems. Maintained by Anthropic since its founding in 2024 and released under the Apache 2.0 license, MCP functions as a universal interface—analogous to USB-C for electronic devices—enabling AI assistants such as Claude and ChatGPT to connect to data sources, tools, and workflows. The protocol uses JSON-RPC over standard input/output and Streamable HTTP transports, and MCP servers expose three categories of capabilities: tools (executable functions), resources (file-like data), and prompts (pre-written templates). The standard is reportedly reaching approximately one-quarter of global professional software developers through native integrations with the dominant AI assistants and development tools.

The product ecosystem includes official SDKs in ten programming languages across three maturity tiers (TypeScript, Python, C#, and Go as Tier 1; Java and Rust as Tier 2; Swift, Ruby, PHP, and Kotlin as Tier 3), developer tools such as the MCP Inspector and a comprehensive debugging guide, and a centralized MCP Registry for server discovery and publishing. Extensions to the core protocol address enterprise needs (OAuth 2.1 authorization, OIDC-flavored refresh tokens, identity provider policy controls) and user experience (MCP Apps for interactive UI rendered inside AI hosts, MCP Tasks for asynchronous operations, and MCP Server Cards for capability metadata). Anthropic's May 2026 acquisition of Stainless—a developer tools company providing SDK services to OpenAI, Meta, and Cloudflare—for over $300 million consolidated exclusive SDK generation infrastructure into Anthropic's platform engineering division alongside MCP.

MCP operates without a traditional revenue model. It is provided as free, open-source infrastructure to AI application developers and enterprise organizations, with no licensing fees or commercial pricing. Distribution is entirely community-led and API-first: developers discover the protocol through documentation, GitHub repositories, and the MCP Registry, and build MCP servers that expose tools for consumption by MCP-compatible clients. The customer base comprises AI application developers (primary segment) building servers, clients, and agents, and enterprise organizations (secondary segment) deploying MCP for secure internal AI-to-system integrations. Anthropic retains primary ownership and stewardship of the protocol's development direction, and no external investors, institutional funding rounds, or public ownership structures are disclosed for MCP itself.

Name

Model Context Protocol

Legal name

Model Context Protocol

Website

https://modelcontextprotocol.io

Company type

Private

Founded year

2024

Operating status

Operating

Headcount range

1–10 employees

Short description

Model Context Protocol is an open-source standard enabling AI applications like Claude and ChatGPT to connect to external data sources, tools, and workflows through a unified interface. Maintained by Anthropic, it provides SDKs in ten programming languages and a server registry.

Ownership category

akta.pro rank

Product category

AI Integration Protocol

NAICS

Computer Systems Design and Related Services (54151), Computer Systems Design Services (541512)

SIC

Services-Computer Integrated Systems Design (7373)

akta.pro primary industry

Data Security & Access Governance for Data (Entitlements/Policy Enforcement) (HDAEADAH)

Keywords

• Open-source protocol
• AI integration standard
• Developer SDKs
• AI connectivity layer
• Agent infrastructure

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Infrastructure, Marketing or Sales

Revenue model

1. Open Source Protocol: MCP is an open-source protocol provided free of charge. The protocol is maintained by Anthropic as part of its platform engineering division and is supported across the AI ecosystem.

Pricing tiers

Go-to-market motion2 records

Distribution channels3 records

Marketing channels4 records

Core offering

Model Context Protocol (MCP) is an open-source standard that enables AI applications such as Claude and ChatGPT to connect to external data sources (local files, databases), tools (search engines, calculators), and workflows through a uniform JSON-RPC interface. The offering comprises the protocol specification, official SDKs in multiple programming languages, a registry for server discovery, and developer tooling for building and testing MCP-compatible integrations.

Product overview

Model Context Protocol (MCP) is an open-source protocol that serves as a standardized connection layer for AI applications. The core product is the MCP specification itself, which enables AI assistants like Claude and ChatGPT to connect to external data sources, tools, and workflows. The ecosystem includes official SDKs in 10 programming languages (TypeScript, Python, C#, Go, Java, Rust, Swift, Ruby, PHP, Kotlin), developer tools (MCP Inspector, Debugging Guide), the MCP Registry for server discovery, and extensions for authorization, tasks, and interactive UI applications. MCP functions as the connectivity infrastructure—analogous to USB-C for AI—rather than an AI capability itself.

Differentiator

Problem solved

Functional benefit

Products and services

• Model Context Protocol (MCP) Open-source protocol standard that enables AI applications like Claude and ChatGPT to connect to external data sources (local files, databases), tools (search engines, calculators), and workflows through a unified JSON-RPC interface. Functions as a USB-C-equivalent connectivity layer for AI assistants.
• MCP Official SDKs Family of official SDK packages for building MCP servers and clients: Tier 1 TypeScript/JavaScript, Python, C#/.NET, Go; Tier 2 Java (with Spring Boot integration), Rust; Tier 3 Swift, Ruby, PHP, Kotlin. Distributed via npm, PyPI, NuGet, Maven/Gradle, crates.io, and other language-specific package managers.
• MCP Inspector Interactive developer tool for testing and debugging MCP servers, supporting both stdio and Streamable HTTP transports with features for inspecting resources, prompts, and tools.
• MCP Registry Official registry at registry.modelcontextprotocol.io for discovering and publishing MCP servers, supporting npm and PyPI package types with authentication and moderation policies, enabling ecosystem growth and server discoverability.
• MCP Reference Servers Official example MCP servers including Everything (reference/test), Fetch (web content), Filesystem (secure file operations with configurable access controls), Git (repository operations), Memory (knowledge graph-based persistent memory), Sequential Thinking (dynamic problem-solving), and Time (timezone conversion).
• MCP Authorization Extensions Supplementary authorization mechanisms including OAuth 2.1, OAuth client credentials flow, and enterprise-managed authorization via identity providers, designed for secure MCP deployments in enterprise environments.
• MCP Apps Interactive UI applications that render inside MCP hosts like Claude Desktop, enabling widgets, forms, pickers, charts, and live dashboards embedded in AI conversations.
• MCP Tasks Extension Extension for asynchronous task execution enabling long-running MCP operations.
• MCP Server Cards Specification extension for describing MCP server capabilities and metadata to enable server discovery.
• Agent Skills for MCP Portable instruction sets (build-mcp-server, build-mcp-app, build-mcpb) that guide AI coding assistants through MCP server design and implementation.

Quantifiable outcome

• Build once, integrate everywhere - MCP servers work across all major AI clients without modification

Named customers4 records

Segments2 records

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Integration6 records

AI capability1 record

Feature5 records

Partnerships

Four partnerships are on record, tiered core.

• Anthropic Claude Plugins OfficialcoreStrategic or Co-development Partner · 1 January 2025Anthropic provides official agent skills plugins (mcp-server-dev) including build-mcp-server, build-mcp-app, and build-mcpb skills that guide AI coding assistants through MCP server design and implementation.
• Anthropic (Claude)coreTechnology or Integration · 1 January 2024Anthropic maintains MCP as part of its platform engineering division and Claude (Anthropic's AI assistant) is a primary MCP client. Claude Desktop uses MCP to connect to local servers, enabling file system access and tool integrations. Anthropic acquired Stainless in May 2026 to strengthen MCP infrastructure.
• OpenAI (ChatGPT)coreTechnology or Integration · 1 January 2024OpenAI supports MCP in ChatGPT, enabling AI assistants to connect to external tools and data sources through the MCP standard. This integration brings MCP to OpenAI's user base.
• Microsoft (Visual Studio Code)coreTechnology or Integration · 1 January 2024Microsoft's VS Code with Copilot Chat supports MCP servers, enabling developers to extend AI coding assistant capabilities through the MCP protocol.

Scale indicators2 records

Recent moves6 records

Expansion highlights5 records

Emerging players

• LangChain: Provides an open-source framework and standard patterns for building LLM-powered applications and agent tool-calling. LangChain's tool/agent abstractions partially overlap with MCP's role of connecting AI models to external tools, and it is a competing approach to the integration problem MCP addresses.
• A2A (Agent-to-Agent) Protocol: An emerging open protocol — backed by Google and a growing coalition — for inter-agent communication. A2A is the most direct competing standard to MCP in the agent-infrastructure layer, and its trajectory relative to MCP will determine the long-term standards landscape.
• Semantic Kernel (Microsoft): Microsoft's open-source SDK for integrating AI models into .NET applications via planners, memory, and connectors. Semantic Kernel addresses similar AI-integration problems as MCP, with Microsoft also being an MCP client (VS Code Copilot), making it both a peer and a participant in the MCP ecosystem.

Direct peers

• gRPC (Google / CNCF): An open-source, high-performance RPC framework governed by the CNCF. Like MCP, gRPC is a protocol standard for inter-process communication with multi-language SDK support, and serves as a comparable model of how an open protocol can achieve cross-vendor adoption.
• OpenAPI Initiative (Linux Foundation): Stewards the OpenAPI Specification, the dominant open standard for describing REST APIs. MCP plays an analogous role for AI-to-tool connectivity, and both function as open, community-driven protocol standards with broad multi-vendor adoption.
• GraphQL Foundation (Linux Foundation): Maintains the GraphQL specification under the Linux Foundation. GraphQL is a widely adopted open standard for API data querying, and serves as a structural analog to MCP: both are open, vendor-neutral protocol standards that emerged to solve integration fragmentation.

Broad incumbents

• Apache Kafka: An open-source distributed event streaming platform under the Apache Software Foundation. Kafka is a comparable open-standard infrastructure project that became default infrastructure for data streaming — a useful analog for MCP's potential trajectory as default AI connectivity infrastructure.
• Hugging Face Transformers: The dominant open-source hub and library for AI models, datasets, and tools. Hugging Face's 'tool-calling' and 'agents' capabilities partially overlap with MCP's integration thesis, and it represents a broader incumbent in the open AI ecosystem that MCP operates within.
• OpenAI Function Calling / Tools API: OpenAI's proprietary mechanism for connecting GPT models to external tools and functions. While not open-source, it competes directly with MCP for the role of standardizing AI-to-tool integration, and OpenAI's decision to also support MCP signals the strategic relevance of this peer.
• Zapier: A long-established integration platform connecting SaaS applications via a standardized action/Trigger interface. Zapier is comparable to MCP in solving application-to-application connectivity, and is increasingly building MCP server integrations to participate in the agent ecosystem.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• GitHubgithub.com/modelcontextprotocol
• LinkedInlinkedin.com/company/modelcontextprotocol

Revenue estimate

Valuation estimate

Number of profiles

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Model Context Protocol