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MCP MCP Projects

@manojshipra

Repository

Basic information

Category

Other

Transports

stdio

Author

manojshipra

About MCP MCP Projects

In this Repo I am learning and practically implementing MCP clients and servers in python.

MCP MCP Projects config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "MCP-Model-Context-Protocol-Projects": {
      "command": "python3",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP MCP Projects tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP-Model-Context-Protocol-Projects?

MCP-Model-Context-Protocol-Projects is a multimodal assistant client built on the Model-Context-Protocol (MCP) framework. It provides tools for executing Python code in a sandboxed environment, querying live weather via Server-Sent Events (SSE), and interacting with MCP servers through a Streamlit-based user interface.

How to use MCP-Model-Context-Protocol-Projects?

After cloning the repository and installing dependencies with pip install -r requirements.txt, create a .env file in the mcp-client folder containing your GROQ_API_KEY. Run the weather SSE tool from the mcp-server folder with python3 weather.py, or launch the interactive UI from the mcp-client folder with streamlit run main.py.

Key features of MCP-Model-Context-Protocol-Projects

  • Weather SSE Tool for live weather updates.
  • Streamlit front-end for querying MCP servers.
  • Python Executor for sandboxed code execution.
  • Relies on the Model-Context-Protocol framework.

Use cases of MCP-Model-Context-Protocol-Projects

  • Query live weather data streamed via MCP SSE servers.
  • Execute isolated Python code through MCP’s sandbox tool.
  • Interact with MCP servers using an intuitive Streamlit UI.
  • Prototype multimodal AI assistants that combine code and data.

Frequently asked questions

1

What prerequisites are needed to run MCP-Model-Context-Protocol-Projects?

You need Python 3.9 or later, `pip`, and a valid Groq API key.

2

How do I configure my API key?

Create a `.env` file in the `mcp-client` folder containing `GROQ_API_KEY=your_groq_api_key_here`.

3

How do I run the weather SSE tool?

Navigate to the `mcp-server` folder and execute `python3 weather.py`.

4

How do I launch the Streamlit UI?

From the `mcp-client` folder, run `streamlit run main.py`.

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