Let's Learn About MCP Together
a year ago
- #AI
- #LLM
- #MCP
- Model Context Protocol (MCP) is a standardized way for large language models (LLMs) to interact with external services.
- MCP was developed by Anthropic, the company behind Claude, and released in late November 2024.
- MCP servers act as interpreters, allowing LLMs (MCP clients) to communicate with services via the MCP protocol.
- Each service that wants to interact with an LLM has its own MCP server, which exposes tools, resources, and prompts to the LLM.
- MCP servers can be built from scratch using SDKs or auto-generated from API endpoints using tools like Speakeasy or FastAPI MCP.
- When writing an MCP server, it's important to optimize for LLM performance by limiting context size, reducing API choices, and providing clear documentation.
- MCP enables new workflows by standardizing how LLMs interact with services, eliminating the need for LLM-specific integrations.
- Dynatrace has released its own MCP server, showcasing potential use cases in observability and other fields.