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MCP Client Streamlit Interface

MCP Client Streamlit Interface

github.com/zeeshanuniqueFrameworks & SDKs3Updated 82w ago
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About MCP Client Streamlit Interface

A web interface for MCP client interaction using Streamlit. Users configure a server script path, enter queries, and view responses from MCP services in a browser.

Key features

  1. 01Web interface for MCP interaction
  2. 02Configurable server script path
  3. 03Real-time query processing
  4. 04API key management

Use cases

  1. 01Test MCP services without command line
  2. 02Interactive exploration of MCP servers
  3. 03Optional web search capability

MCP support

Streamlit-based MCP client that communicates with MCP services and displays responses through a browser interface.

Details

From the project README

MCP Client Streamlit Interface

A simple Streamlit interface for interacting with the MCP client.

Setup

  1. Make sure you have Python 3.13+ installed
  2. Install the dependencies: 
    pip install -e .
  3. Create a .env file with your API keys: 
    GEMINI_API_KEY=your_gemini_api_key
SERPAPI_KEY=your_serpapi_key  # Optional for web search functionality

Running the Streamlit Interface

Run the following command to start the Streamlit interface:

streamlit run main.py

Then open your browser to http://localhost:8501 to interact with the MCP client.

Usage

  1. Enter the path to the server script (default is server.py)
  2. Type your query in the text area
  3. Click "Process Query" to send the query to the MCP client
  4. View the response from the MCP client

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.