What is MCP (Model Context Protocol)?
MCP (Model Context Protocol) is an open standard by Anthropic that allows AI agents to connect to external tools and data sources through a standardised interface — without custom integration code.
What it is
MCP (Model Context Protocol) is an open standard developed by Anthropic that allows AI agents to connect to external tools, data sources, and services through a standardised interface — enabling agents to take actions across multiple platforms without custom integration code for each connection.
How it works
MCP works like USB for AI agents. MCP servers expose capabilities (tools, resources, prompts) that agents can discover and use. MCP clients (the AI agents) connect to these servers and call the exposed functions. This architecture lets agents dynamically discover what tools are available and use them appropriately. Developers publish MCP servers for their products; AI agents that support MCP can immediately use those capabilities.
Key capabilities
- ✓Standardised 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 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×M integration problem — where N agents each needed custom integrations with M tools, requiring N×M engineering efforts. MCP reduces this to N+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. Hundreds 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 with each other). Both are needed for full multi-agent orchestration.
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