A Streamlit application that provides a chat interface for interacting with MCP (Model Context Protocol) servers. This app allows you to configure multiple MCP servers and chat with them using natural language.

Tech stack:

mcp-use to connect LLM to MCP servers
Stagehand MCP for browser access
Firecrawl MCP for scraping
Ragie MCP for multimodal RAG
Graphiti MCP as memory
Terminal & GitIngest MCP

Setup

Install Dependencies:
```
uv sync 
```

Environment Variables: Create a .env file with your API keys:

OPENAI_API_KEY=your-openai-api-key
FIRECRAWL_API_KEY=your-firecrawl-api-key
RAGIE_API_KEY=your-ragie-api-key

Setup MCP Servers

Go to server.py and update the paths to the MCP servers according to your system.
Run the App:
```
streamlit run mcp_streamlit_app.py
```

Usage

Configure MCP Servers:
- Use the sidebar to enter your MCP server configuration in JSON format
- Click "Load Example Config" to see a sample configuration
- Click "Activate Configuration" to initialize the MCP client
Chat with MCP Tools:
- Once configured, use the chat interface to interact with your MCP servers
- Ask questions about available tools or request specific actions
- The agent will use the appropriate MCP tools to respond

Example Configuration

{
  "mcpServers": {
    "stagehand": {
      "command": "node",
      "args": ["/path/to/stagehand/dist/index.js"],
      "env": {
        "OPENAI_API_KEY": "your-api-key",
        "LOCAL_CDP_URL": "http://localhost:9222"
      }
    },
    "firecrawl": {
      "command": "npx",
      "args": ["-y", "firecrawl-mcp"],
      "env": {
        "FIRECRAWL_API_KEY": "your-firecrawl-key"
      }
    }
  }
}

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Contribution

Contributions are welcome! Please fork the repository and submit a pull request with your improvements.

README.md

MCP-powered Ultimate AI Assistant

Setup

Usage

Example Configuration

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Contribution