A powerful AI agent chatbot that leverages external tools through the Model Context Protocol (MCP) to extend its capabilities beyond traditional language models.
# Install Smart Agent
pip install smart-agent
# For web interface (Chainlit), install with web extras
pip install smart-agent[web]
# Initialize configuration
smart-agent init
# Start the CLI chat interface (connects to remote tools by default)
smart-agent chat
# OR start the web interface
smart-agent chainlit
# If you need to run your own tools locally:
smart-agent start # Start the server componentsSmart Agent operates in two primary modes:
Client mode provides chat interfaces that connect to MCP servers (either local or remote).
- What it does: Provides CLI or web interfaces to interact with the agent
- When to use: When you want to chat with the agent using available tools
# CLI interface
smart-agent chat
# Web interface (Chainlit)
smart-agent chainlitServer mode manages MCP (Model Context Protocol) servers that provide tools and capabilities to the agent.
- What it does: Launches and manages tool servers that expose capabilities through standardized endpoints
- When to use: When you need to run tools locally or host tools for remote clients
# Start all server components (tools and LLM proxy)
smart-agent start
# Check status of running services
smart-agent status
# Stop all services
smart-agent stopSmart Agent supports two primary connection types between clients and servers:
- How it works: Direct communication through standard input/output
- When to use: For tools running locally on the same machine
- Configuration: Use
transport: stdioin your config
- How it works: Communication via Server-Sent Events over HTTP/HTTPS
- When to use: For connecting to tools running on remote machines
- Configuration: Use
transport: ssein your config
Smart Agent provides conversion mechanisms between transport types:
-
stdio_to_sse: Converts local stdio tools to SSE endpoints
- Useful for exposing local tools as network services
- Example:
transport: stdio_to_ssein config
-
sse_to_stdio: Converts remote SSE endpoints to local stdio
- Useful for using remote tools as if they were local
- Example:
transport: sse_to_stdioin config
# config.yaml
llm:
base_url: "http://localhost:4000"
model: "claude-3-7-sonnet-20240229"
api_key: "api_key"
temperature: 0.0
tools:
# Remote tool with sse conversion
mcp_tool_1:
enabled: true
url: "http://{HOST}:{PORT}/sse"
transport: sse
# Local tool
mcp_tool_2:
enabled: true
command: "uvx mcp-think --transport stdio"
transport: stdio# Initialize configuration
smart-agent init
# Edit config.yaml to use remote URLs
# Example: url: "https://api.remote-tool.com/sse"
# Start client interface - will automatically connect to remote tools
smart-agent chat # or chainlit# Initialize configuration
smart-agent init
# Start server components
smart-agent start
# Start client interface
smart-agent chat # or chainlit- Python 3.9+
- Node.js and npm (for running tools via supergateway)
- Docker (optional, for container-based tools)
- API keys for language models
# Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install from PyPI
pip install smart-agent
# For web interface (Chainlit)
pip install smart-agent[web]
# For monitoring features
pip install smart-agent[monitoring]For more detailed information, see the documentation.