Rasa MCP Tools API Reference | Rasa Documentation

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Rasa MCP Tools are included in Rasa Pro 3.16 and later.

v3.16

Cheat Sheet

Tool	Group	What it does
`search_rasa_documentation`	Documentation	Search official Rasa docs
`list_project_flow_definitions`	Introspection	List all flows
`list_project_slot_definitions`	Introspection	List all slots
`list_project_response_definitions`	Introspection	List all responses
`get_flow`	Introspection	Get one flow by ID or name
`get_slot`	Introspection	Get one slot by name
`get_response`	Introspection	Get one response by name
`list_project_custom_actions_in_domain`	Introspection	List custom actions declared in domain
`list_custom_action_implementations`	Introspection	List custom action Python classes
`list_default_action_names`	Introspection	List built-in Rasa action names
`get_flow_schema`	Schemas	Get the flow JSON schema
`get_domain_schema`	Schemas	Get the domain YAML schema
`get_e2e_schema`	Schemas	Get the E2E test YAML schema
`validate_project`	Build	Validate project config and data
`train_rasa_assistant`	Build	Train the assistant model
`talk_to_assistant`	Runtime	Send messages to the running assistant
`get_assistant_logs`	Runtime	Get recent assistant logs
`validate_scenario`	Evaluation	Validate a scenario YAML before running
`evaluate_agent`	Evaluation	Run a simulated evaluation scenario

CLI Commands

Command	Effect
`rasa tools init`	Interactive setup wizard. Creates `.rasa/tools.yaml` and downloads offline docs and skills.
`rasa tools init -y`	Non-interactive setup with all defaults.
`rasa tools init --project-path PATH`	Initialize for a project in a different directory.
`rasa tools init docs`	Download or refresh offline documentation files.
`rasa tools run --mode stdio`	Start the MCP server in stdio mode (for IDE integrations).
`rasa tools run --mode http --port 7331`	Start the MCP server in HTTP mode on the specified port.
`rasa tools run --config PATH`	Start the server using settings from `.rasa/tools.yaml` in the given directory.
`rasa tools run --project-path PATH`	Override the project folder the server reads from.
`rasa tools run --rasa-server-url URL`	Override the Rasa server URL (default: `http://localhost:5005`).

Documentation tools

`search_rasa_documentation`

Search the official Rasa documentation for authoritative information. Returns relevant documentation about Rasa concepts, APIs, best practices, configuration, and troubleshooting with links to official docs.

Parameter	Type	Required	Description
`query`	string	yes	The search query to find relevant Rasa documentation entries.

Returns: Matching documentation snippets with source links.

Sample prompts:

Search the Rasa docs for how to configure slot validation.

Look up how collect steps work in Rasa flows.

`list_project_flow_definitions`

List all flow definitions in the project. Returns flow ID, name, and file path for each flow.

Parameter	Type	Required	Default	Description
`data_folder`	string	no	`"data"`	Folder containing flow YAML files, relative to project root.

Returns: List of flows with id, name, and file_path.

Sample prompt:

List all flows in this project.

`list_project_slot_definitions`

List all slot definitions from the project domain file(s). Returns slot name, type, and file path.

Parameter	Type	Required	Default	Description
`domain_folder`	string	no	`"domain"`	Folder containing domain YAML files, relative to project root.

Returns: List of slots with name, type, and file_path.

Sample prompt:

List all slots in this project and their types.

`list_project_response_definitions`

List all response (utterance) definitions from the project domain file(s). Returns response name and file path.

Returns: List of responses with name and file_path.

Sample prompt:

Show me all responses defined in this project.

`get_flow`

Get a single flow by flow ID (YAML key) or flow name. Returns flow metadata and full definition including steps, triggers, and branching logic.

Parameter	Type	Required	Default	Description
`flow_id`	string	yes	—	Flow ID (YAML key) or human-readable flow name.
`data_folder`	string	no	`"data"`	Folder containing flow YAML files.

Returns: Full flow definition with metadata.

Sample prompt:

Get the transfer_money flow and explain its steps.

`get_slot`

Get a single slot by name. Returns slot metadata and full definition from the domain.

Parameter	Type	Required	Default	Description
`slot_name`	string	yes	—	Slot name.
`domain_folder`	string	no	`"domain"`	Folder containing domain YAML files.

Returns: Full slot definition with type, mappings, and metadata.

Sample prompt:

Get the recipient slot definition and explain its mappings.

`get_response`

Get a single response (utterance) by name. Returns response metadata and full definition including text, images, buttons, and custom payloads.

Parameter	Type	Required	Default	Description
`response_name`	string	yes	—	Response name (e.g. `utter_greet`).
`domain_folder`	string	no	`"domain"`	Folder containing domain YAML files.

Returns: Full response definition with all variations.

Sample prompt:

Get the utter_ask_recipient response.

`list_project_custom_actions_in_domain`

List all custom actions declared in the domain file(s). Returns action name and file path where the action is registered.

Parameter	Type	Required	Default	Description
`domain_folder`	string	no	`"domain"`	Folder containing domain YAML files.

Returns: List of custom action names with name and file_path. This lists domain declarations, not Python implementations.

Sample prompt:

What custom actions are declared in the domain?

`list_custom_action_implementations`

List all custom action Python implementations in the project. Returns action name, class name, and file path for each action.

Parameter	Type	Required	Default	Description
`actions_folder`	string	no	auto-detected	Path to the actions folder relative to project root. Auto-detects from `endpoints.yml` or defaults to `"actions"`.

Returns: List of action implementations with action_name, class_name, and file_path.

Notes:

If error is set: the actions folder was not found. Check endpoints.yml or specify the folder.
If count=0 and no error: the actions folder exists but contains no action classes.

Sample prompt:

List all custom action implementations and their file locations.

`list_default_action_names`

List all built-in default action names provided by Rasa. These actions are available without configuration and can be overridden.

Parameters: None.

Returns: List of default action name strings.

Sample prompt:

What are the default built-in Rasa actions?

Schema tools

`get_flow_schema`

Get the official Rasa flow schema in JSON Schema format. Use this to validate flow YAML or generate new flows.

Parameter	Type	Required	Default	Description
`calm_only`	boolean	no	`true`	Return only CALM-related properties, excluding NLU-specific fields.

Returns: JSON Schema document describing flow structure: name, description, step types, branching logic (if/then/else), collect steps, flow guards, and more.

Sample prompt:

Get the flow schema so I can write a valid new flow.

`get_domain_schema`

Get the official Rasa domain schema in YAML schema format. Use this to validate domain YAML or generate domain files.

Returns: YAML schema document describing domain structure: slots, custom actions, responses, and more.

Sample prompt:

Get the domain schema. I need to add a new boolean slot correctly.

`get_e2e_schema`

Get the official Rasa E2E test schema in YAML schema format. Use this to validate or generate end-to-end test files.

Parameters: None.

Returns: YAML schema document describing E2E test structure: test cases, steps (user and bot messages), fixtures, metadata, stub custom actions, and assertions.

Sample prompt:

Get the E2E test schema, then write tests for the transfer_money flow.

Build and validation tools

`validate_project`

Validate the assistant project configuration and training data. Runs comprehensive checks on domain, flows, config, and training data.

Parameters: None (reads from the configured project folder).

Returns: Pass/fail status with a list of errors and warnings.

Notes:

Can take 60+ seconds for large projects.
Always run this after making changes and before training.

Sample prompts:

Validate this project and tell me what's wrong.

I made changes to the domain. Validate and fix any issues.

`train_rasa_assistant`

Train the Rasa assistant with the current project configuration. Creates a new model in the models/ directory.

Parameters: None (reads from the configured project folder).

Returns: Training status (success/failure), model path, and any errors.

Notes:

Can take several minutes for large projects.
Only call this after validation passes.
Each training run produces a new timestamped model file.

Sample prompts:

Train the assistant.

Validate and then train. If validation fails, fix the issues first.

Runtime testing and debugging tools

`talk_to_assistant`

Test the assistant by sending a sequence of messages and verifying responses. Creates a new conversation for each call.

Parameter	Type	Required	Default	Description
`messages`	list[string]	yes	—	List of user messages to send in sequence. Each message is sent after the assistant responds to the previous one.
`rasa_server_url`	string	no	`http://localhost:5005`	Override the Rasa server URL. Leave empty to use the configured default.

Returns: Structured response with:

Conversation history (user messages and assistant responses)
Tracker context showing conversation state, active flows, and slot values

Prerequisites: The Rasa assistant must be running (rasa run or rasa run --inspect).

Sample prompts:

Talk to the assistant: "I want to send money", "to Jen", "50 dollars", "yes".
Verify the transfer_money flow completes successfully.

Test the happy path: send "hello" then "I need to transfer money to Bob".
Check which flow was triggered and what slots were filled.

`get_assistant_logs`

Get recent log entries from the Rasa assistant for troubleshooting.

Parameters: None.

Returns: Recent log entries as text.

Sample prompts:

Get the assistant logs and explain why the last conversation failed.

Show me the assistant logs. I think a custom action is throwing an error.

Simulation and evaluation tools

`validate_scenario`

Validate a scenario YAML file before running any simulation. Checks syntax and structure, assertion type validity, and that all slot names referenced in initial_slots, slot_was_set, and slot_was_not_set assertions exist in the domain with compatible types. All errors are reported together in a single response.

Parameter	Type	Required	Default	Description
`scenario_path`	string	yes	—	Relative path to the scenario YAML file within the project (e.g. `eval/scenarios/happy_path.yml`).
`domain_folder`	string	no	`"domain"`	Folder containing domain YAML files, relative to project root. Used to verify slot names and types.

Returns: Pass/fail status with a list of all validation errors.

Sample prompts:

Validate the scenario at eval/scenarios/order_delay.yml.

I just edited a scenario file. Check it for errors before running.

`evaluate_agent`

Run a simulation and evaluation loop for a given scenario. Loads eval/conftest.yml, simulates a multi-turn conversation with an LLM-based user against the running Rasa server, evaluates deterministic assertions against the tracker event history, and scores quality criteria and metrics with an LLM judge. Writes per-run result files and updates the experiment summary.

Parameter	Type	Required	Default	Description
`scenario_path`	string	yes	—	Relative path to the scenario YAML file within the project.
`experiment_timestamp`	string	yes	—	Experiment folder name (e.g. `2026-04-21_14-30-22`). Generate once per session with `datetime.now().strftime('%Y-%m-%d_%H-%M-%S')` and reuse across all scenarios so they land under the same folder.
`run_count`	integer	no	`1`	Number of times to run the scenario. Multiple runs surface LLM non-determinism. Capped at 10.
`rasa_server_url`	string	no	configured default	Override the Rasa server URL. Leave empty to use the server URL configured at startup.

Returns: Pass/fail verdict, runs passed/total count, and the path to the updated summary.txt.

Prerequisites: The Rasa assistant must be running (rasa run --inspect recommended so that simulated conversations are viewable in the Inspector).

Notes:

A run is marked failed if any deterministic assertion fails or any quality criterion fails.
Quality metrics (task_completion and aggregated bot_quality — helpfulness, repair_quality, coherence, tone) are informational and do not gate the pass/fail verdict.
On timeout, completed run_N.txt files are preserved but summary.txt is not updated.

Sample prompts:

Generate and run a happy path scenario for the add_contact flow.

Run the order_delay scenario 3 times and summarize the results.

Run all scenarios in eval/scenarios/ and tell me which ones failed.

Typical workflow

A common sequence for building a feature end-to-end:

Discover — list_project_flow_definitions, list_project_slot_definitions, list_project_response_definitions
Understand schemas — get_flow_schema, get_domain_schema, get_e2e_schema
Implement — write flows, domain entries, and custom actions
Validate — validate_project
Train — train_rasa_assistant
Test — talk_to_assistant
Debug — get_assistant_logs if behavior is unexpected
Evaluate — validate_scenario, evaluate_agent to run LLM-simulated conversations and score them against your goals