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mcp-projects

Open-Source Projects Repo for MCP (Model Context Protocol).

Steps to install and run:

  1. Clone this repo
  2. Install the requirements
    pip install mcp fastapi uvicorn fastapi-mcp llama-index llama-index-embeddings-huggingface llama-index-llms-langchain langchain-mcp-adapters mcp-use
    
  3. Make a .env file in the root folder with the following credentials:
    API_KEY=<IBM_cloud_API_Key>
    PROJECT_ID=<Watsonx_Project_id>
    IBM_CLOUD_URL=<IBM cloud url>
    
    MODEL_ID=<your watsonx.ai LLM id>
    
    TAVILY_API_KEY=<your Tavily api key for web search>
    
    or, use your own llm provider - its agnostic to the projects (few changes needs to be done though)
    
  4. Experiment with different projects and files
    • make sure to run the mcp servers first and then only
    • run the clients

What is Model Context Protocol (MCP)?

At its core, MCP is a standardized way for applications to provide AI models with richer context about their environment, user preferences, and conversation history. Think of it as a smart, structured way to feed memory and context to AI systems.

MCP Structure

The Problem MCP Solves

Current AI systems have limited "working memory" - they can only see a certain amount of conversation history at once (their "context window"). Imagine trying to have a conversation with someone who only remembers the last few exchanges:

  • You: "Remember that project we discussed last week about optimizing the supply chain?"
  • AI without good context: "I don't recall that specific discussion. Could you remind me of the details?"

This limitation forces users to constantly re-explain things, leading to frustrating interactions. MCP aims to solve this by creating a structured method for maintaining and accessing context.

Some Analogies

1. GPS Navigation

Traditional AI context management is like giving someone directions one turn at a time, without showing them the full map. If they forget a step, the journey breaks down.

MCP is like a GPS navigation system that:

  • Knows your destination
  • Remembers your preferred routes
  • Adjusts based on real-time conditions
  • Always knows exactly where you are in the journey

Read this medium article for comprehensive understanding of MCP: Understanding Model Context Protocol (MCP): A Layman’s Guide

Do make Pull Requests to contribute to this asset ✨

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