These servers aim to demonstrate mcp features and the official sdks Mcp llm an mcp server that provides access to llms using the llamaindexts library. [1] mcp provides a universal interface for reading files, executing.
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And at the heart of it all sits the mcp server, the part of your application that exposes tools and context to the llm
In this post, we'll dive deep into what the mcp server does, how it works, and how you can build your own
What is an mcp server An mcp server is a standalone process that acts as a context provider for llms. The model context protocol (mcp) provides a standardized way for servers to request llm sampling (“completions” or “generations”) from language models via clients This flow allows clients to maintain control over model access, selection, and permissions while enabling servers to leverage ai capabilities—with no server api keys necessary
Servers can request text, audio, or image. Mcp servers mcp servers are what expose additional functionality and information to your llms Each mcp server will have 1 to many functions that are offered up to each llm An example of an mcp server would be one that has functionality to say provide your llm with the current date and time
Model context protocol (mcp) represents a significant advancement in how we connect ai language models with external data sources and tools
This post is about how mcp figures out which tool to use
