MCP Swarm Agent

mcp-agent implements OpenAI's Swarm pattern for multi-agent workflows, but in a way that can be used with any model provider.

This example is taken from the Swarm repo, and shown to work with MCP servers and Anthropic models (and can of course also work with OpenAI models).

This example demonstrates a multi-agent setup for handling different customer service requests in an airline context using the Swarm framework. The agents can triage requests, handle flight modifications, cancellations, and lost baggage cases.

https://github.com/user-attachments/assets/b314d75d-7945-4de6-965b-7f21eb14a8bd

Agents

1. Triage Agent: Determines the type of request and transfers to the appropriate agent.
2. Flight Modification Agent: Handles requests related to flight modifications, further triaging them into:
   • Flight Cancel Agent: Manages flight cancellation requests.
   • Flight Change Agent: Manages flight change requests.
3. Lost Baggage Agent: Handles lost baggage inquiries.

1 App set up

First, clone the repo and navigate to the workflow swarm example:

git clone https://github.com/lastmile-ai/mcp-agent.git
cd mcp-agent/examples/workflows/workflow_swarm

Install uv (if you don’t have it):

pip install uv

Sync mcp-agent project dependencies:

uv sync

Install requirements specific to this example:

uv pip install -r requirements.txt

2 Set up environment variables

Copy and configure your secrets and env variables:

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

Run your MCP Agent app:

uv run main.py