rasa-setting-up-react-agents

Configuring ReAct Sub Agents

ReAct sub agents are built-in autonomous agents that dynamically choose which MCP tools to invoke based on conversation context. They operate in a ReAct (Reasoning + Acting) loop — the agent reasons about the user's request, picks a tool, observes the result, and repeats until the task is done.

MCP servers must be defined in endpoints.yml before configuring a ReAct sub agent. See the rasa-configuring-mcp-server skill for server setup and authentication.

This feature is in beta and available starting from Rasa 3.14.0.

Workflow

1. Ensure the MCP server is defined in endpoints.yml (see rasa-configuring-mcp-server skill).
2. Create the sub agent directory with a config.yml (see "Directory structure" and "Configuration").
3. Choose between general-purpose or task-specific agent type (see "General-purpose vs task-specific").
4. Optionally filter which MCP tools the agent can access (see "Tool filtering").
5. Invoke the sub agent from a flow using a call step (see "Invoking from a flow").
6. Optionally customize the prompt, input/output processing, or add custom tools (see "Customization").
7. Validate the project.

Directory structure

Each ReAct sub agent lives in its own subdirectory under sub_agents/. Both rasa train and rasa run scan this directory by default; pass --sub-agents <path> to either command to use a different directory.

The agent name must be unique across all sub agents and all flow IDs.

your_project/
├── config.yml
├── endpoints.yml
├── domain/
├── data/flows/
└── sub_agents/
    └── stock_explorer/
        ├── config.yml              # required
        ├── prompt_template.jinja2  # optional
        └── custom_agent.py         # optional

Configuration

The sub agent's config.yml connects the agent to one or more MCP servers defined in endpoints.yml. The protocol defaults to RASA — do not set it to A2A.

# sub_agents/stock_explorer/config.yml
agent:
  name: stock_explorer
  description: "Agent that helps users research and analyze stock options"

configuration:
  llm:                                   # optional, default model is provided by Rasa codebase
    model_group: my_llm
  prompt_template: sub_agents/stock_explorer/prompt_template.jinja2  # optional
  timeout: 30                            # optional, seconds before timing out
  max_retries: 3                         # optional, MCP connection retries
  include_date_time: true                # optional, default: true
  timezone: "America/New_York"           # optional, default: "UTC"

connections:
  mcp_servers:
    - name: trade_server
      include_tools:
        - find_symbol
        - get_company_news
        - fetch_live_price