Protocols
Model Context Protocol (MCP)
An open protocol standardizing how AI applications connect to external data sources, tools, and services. MCP enables AI agents to access real-time information, execute actions, and maintain context across sessions.
Definition
An open protocol standardizing how AI applications connect to external data sources, tools, and services. MCP enables AI agents to access real-time information, execute actions, and maintain context across sessions.
Examples
- Connecting AI agents to external databases via MCP servers
- Integrating file system access for document processing
- Enabling web API calls for real-time data retrieval
Related terms
Read more in our docs
Frequently asked
- What is Model Context Protocol (MCP)?
- An open protocol standardizing how AI applications connect to external data sources, tools, and services. MCP enables AI agents to access real-time information, execute actions, and maintain context across sessions.
- How is Model Context Protocol (MCP) used in practice?
- Model Context Protocol (MCP) is commonly used in scenarios such as: Connecting AI agents to external databases via MCP servers; Integrating file system access for document processing; Enabling web API calls for real-time data retrieval.
- How does yno.ai support Model Context Protocol (MCP)?
- yno.ai integrates Model Context Protocol (MCP) via the Model Context Protocol, so agents can connect to your data and tools securely.
- What other concepts are related to Model Context Protocol (MCP)?
- Model Context Protocol (MCP) relates to Tool Use, Agentic AI, MCP Server. Each links to its own glossary page below.