Sample	Description
01_basic	A basic example of hosting an agent with the `responses` API and carrying on a multi-turn conversation.
02_local_tools	An example of hosting an agent with the `responses` API and local tools including a function tool and a local shell tool.
03_remote_mcp	An example of hosting an agent with the `responses` API and remote MCPs, including a GitHub MCP server and a Foundry Toolboox.
04_workflows	An example of hosting a workflow with the `responses` API.

Running the server locally

Navigate to the sample directory and run the following command to start the server:

python main.py

Interacting with the agent

There two ways to interact with the agent: sending HTTP requests to the server or using the azd CLI:

Invoke with `azd`

azd ai agent invoke --local "Hi"

Sending HTTP requests

Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:

curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "Hi"}'

See the individual samples for more examples of interacting with the agent.

Deploying to a Docker container

Navigate to the sample directory and build the Docker image:

docker build -t hosted-agent-sample .

Run the container, passing in the required environment variables:

docker run -p 8088:8088 \
  -e FOUNDRY_PROJECT_ENDPOINT=<your-endpoint> \
  -e FOUNDRY_MODEL=<your-model> \
  hosted-agent-sample

The server will be available at http://localhost:8088. You can send requests using the same curl command shown above.

Deploying to Foundry

TODO

Using the deployed agent in Agent Framework

After deploying the agent, you can also try to use the agent in Agent Framework. Refer to the using_deployed_agent.py sample for an example of how to do this.

README.md

Hosting agents with Foundry Hosting and the responses API