MCP Search Server

# Streamlit MCP Agent example This Streamlit example shows a "finder" Agent which has access to the 'fetch' and 'filesystem' MCP servers. You can ask it information about local files or URLs, and it will make the determination on what to use at what time to satisfy the request. <img src="https://github.com/user-attachments/assets/7ad27d23-9ed6-4e0e-ba7f-2d3b0afef847" height="512"> --- ```plaintext ┌───────────┐ ┌──────────┐ ┌──────────────┐ │ Streamlit │─────▶│ Finder │──┬──▶│ Fetch │ │ App │ │ Agent │ │ │ MCP Server │ └───────────┘ └──────────┘ │ └──────────────┘ │ ┌──────────────┐ └──▶│ Filesystem │ │ MCP Server │ └──────────────┘ ``` ## `1` App set up First, clone the repo and navigate to the Streamlit MCP Agent example: ```bash git clone https://github.com/lastmile-ai/mcp-agent.git cd mcp-agent/examples/usecase/streamlit_mcp_basic_agent ``` Install `uv` (if you don’t have it): ```bash pip install uv ``` Sync `mcp-agent` project dependencies: ```bash uv sync ``` Install requirements specific to this example: ```bash uv pip install -r requirements.txt ``` ## `2` Set up secrets and environment variables Copy and configure your secrets and env variables: ```bash cp mcp_agent.secrets.yaml.example mcp_agent.secrets.yaml ``` Then open `mcp_agent.secrets.yaml` and add your api key for your preferred LLM. ## `3` Run locally To run this example: With uv: ```bash uv run streamlit run main.py ```