MCPStack is a library for creating Model Context Protocol (MCP) pipelines for LLMs. Basically, MCPStack integrates multiple
MCP tools and data sources into a user-friendly Scikit-learn-line pipeline process for LLMs.
An MCPStack MCP tool can enable conversational AI communication with healthcare databases like MIMIC-IV,
eliminating the need for sophisticated SQL queries and data security concerns.
MCPStack functions similarly to a Scikit-learn toolbox for MCPs, allowing MCPs to be stacked and orchestrated together like
if it was transformers and or estimators in Scikit-learn. Creating complicated workflows allows an LLM to interact
with data, conduct deterministic-based analysis, and generate insights while caring about the visualisation, as they are very good at it.
Finally, why the MCP-Pipeline? MCPStack MCP tools will be stored separately from the orchestrator. As a result,
MCP-Pipeline serves as the repository for both MCPStack our main orchestrator-based library and the MCP tools that come with it.
👉Whatever They Are For, They Are Welcome!
It is easy, and even faster with the MCPStack MCP Tool Template. Broadly speaking what you have to do is to instantiate the right classes, build your actions of interest for the LLMs to play with, and finally, how to configure your MCP via CLI!
Come check out the marketplace of MCPs at the documentation of MCPStack!
Important
Bear With Us! This is a very alpha version of the whole ecosystem, and we are working hard to make it better, one MCP at a time 👀
Cheers! 🍻
