What is MCP (Model Context Protocol)?
Last updated July 9, 2026 by The AI Agent Index Editorial Team
MCP (Model Context Protocol) is an open standard that lets AI agents connect to external tools and data through one unified interface. Definition and examples.
What it is
MCP (Model Context Protocol) is an open standard developed by Anthropic that lets AI agents connect to external tools, data sources, and services through a standardized interface, without custom integration code for each connection. It has two sides: an MCP server exposes capabilities that agents can use, and an MCP client is the agent that connects to those servers. A product can expose a server, act as a client, do both, or neither.
How it works
MCP works like USB for AI agents. MCP servers expose capabilities such as tools, resources, and prompts that agents can discover and use. MCP clients, the AI agents, connect to these servers and call the exposed functions. This lets agents dynamically discover what tools are available and use them appropriately. Developers publish MCP servers for their products, and any MCP-compatible client can immediately use those capabilities. See our separate definitions of an MCP server and an MCP client for how each side works in detail.
Key capabilities
- ✓Standardized tool and data source connections
- ✓Dynamic capability discovery
- ✓Cross-platform agent interoperability
- ✓Reduced integration engineering overhead
- ✓Growing ecosystem of MCP-compatible tools
- ✓Works with any MCP-compatible AI agent
Common use cases
- →Connecting AI agents to CRMs like Salesforce and HubSpot without custom code
- →Giving coding agents access to GitHub, Jira, and documentation tools
- →Enabling research agents to query multiple databases through one interface
- →Building multi-agent systems where agents share tools
- →Rapidly expanding what an AI agent can do by adding MCP servers
How to evaluate one
- ?Does the product expose its own MCP server that other agents can connect to?
- ?Does the AI agent support MCP as a client?
- ?Are there MCP servers available for the tools you use?
- ?How does the platform handle authentication for MCP connections?
- ?Is MCP support native or does it require additional configuration?
- ?What is the latency and reliability of MCP tool calls?
Frequently asked questions
Who created MCP and why?
MCP was created by Anthropic and released as an open standard in late 2024. The goal was to solve the N times M integration problem, where N agents each needed custom integrations with M tools, requiring N times M engineering efforts. MCP reduces this to N plus M: each agent and each tool only needs one MCP implementation.
Which AI agents support MCP?
MCP support has grown rapidly. Claude, Cursor, Windsurf, Zed, and many other AI tools support MCP as clients. Thousands of MCP servers have been published for tools including GitHub, Slack, Notion, Google Drive, Salesforce, and databases.
Is MCP the same as Agent2Agent (A2A)?
No, they are complementary standards. MCP handles agent-to-tool connections, how an agent uses a tool. A2A, developed by Google, handles agent-to-agent communication, how multiple agents coordinate. Both are needed for full multi-agent orchestration.
What is the difference between an MCP server and an MCP client?
An MCP server is exposed by a product so external agents can connect in to its tools and data. An MCP client is a product that connects out to external servers to use their tools. A product can be one, both, or neither, and exposing a server is the scarcer, more valuable signal.
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