The Model Context Protocol (MCP) is an open standard for linking AI models with external tools and data sources. It employs STDIO for local integrations and HTTP for remote interactions. Streamable HTTP, introduced in early 2025, enhances this by enabling continuous, real-time data streaming between clients and servers, moving beyond the traditional HTTP+SSE model. This single-endpoint mechanism simplifies implementation, allowing commands via one URL while supporting bi-directional interactions.
Key phases of MCP’s operation include session establishment, communication channel setup, client requests for streaming responses, and server notifications. It allows for real-time updates during long-running tasks and features robust recovery mechanisms for connection drops using session IDs and event tracking.
In conclusion, Streamable HTTP innovatively combines the power of streaming with existing HTTP infrastructure, enhancing the usability of AI tools. This evolution marks a significant step toward effective, dynamic integrations between AI agents and external applications.
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