Rasa Calling MCP Tools From Flows

Calling MCP Tools from Flows

MCP tools can be invoked directly from flow steps using a call step with explicit input/output mappings. This replaces the need for custom action code when you only need to call an external API.

MCP servers must be defined in endpoints.yml before calling their tools. 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.

When to use MCP vs a custom action

Use an MCP tool call when:

• The tool already exists on an MCP server
• You just need to pass slot values in and store results back
• No complex logic around the call (branching, retries, multiple sequential API calls)

Use a custom action instead when:

• You need complex business logic (multiple API calls, conditionals, error handling)
• You need access to the full tracker (conversation history, events, sender ID)
• You need to send custom messages via the dispatcher
• The data transformation can't be expressed in a Jinja2 output mapping
• The external API isn't exposed via MCP

See rasa-writing-custom-actions for custom action guidance.

Workflow

1. Ensure the MCP server is defined in endpoints.yml (see rasa-configuring-mcp-server skill).
2. Call the MCP tool from a flow using a call step with mcp_server and mapping (see "Calling an MCP tool from a flow").
3. Map tool results to slots, handling both structured and unstructured output (see "Tool result formats").
4. Validate the project.

Calling an MCP tool from a flow

Use a call step with mcp_server and mapping to invoke a tool directly.

flows:
  buy_order:
    description: helps users place a buy order for a particular stock
    steps:
      - collect: stock_name
      - collect: order_quantity
      - action: check_feasibility
        next:
          - if: slots.order_feasible is True
            then:
              - call: place_buy_order
                mcp_server: trade_server
                mapping:
                  input:
                    - param: ticker_symbol
                      slot: stock_name
                    - param: quantity
                      slot: order_quantity
                  output:
                    - slot: order_status
                      value: result.structuredContent.order_status.success
          - else:
              - action: utter_invalid_order
                next: END

Tool result formats

MCP tools return results in one of two formats. Handle both in your output mapping.

Structured content

When the tool defines an output schema, Rasa returns structured data. Access specific values using dot notation in the value field:

# Tool returns: {"result": {"structuredContent": {"order_status": {"success": true, "order_id": "abc123"}}}}
output:
  - slot: order_status
    value: result.structuredContent.order_status.success
  - slot: order_id
    value: result.structuredContent.order_status.order_id

Unstructured content

When the tool has no output schema, the entire result is a serialized string. Capture it in a single slot for downstream processing:

# Tool returns: {"result": {"content": [{"type": "text", "text": "{\"order_status\": ...}"}]}}
output:
  - slot: order_data
    value: result.content

Common pitfalls

• MCP server name mismatch — the mcp_server value in a flow call step must exactly match a name in endpoints.yml. A typo means the call fails at runtime with no compile-time warning.
• Missing tool on server — if the tool name in call doesn't exist on the referenced MCP server, the call fails at runtime.
• Ignoring unstructured content — when a tool has no output schema, results come back as a serialized string under result.content, not as result.structuredContent. Always account for both formats.