Rasa MCP Tools | Rasa Documentation

Build your first agent in just a few minutes with Rasa Copilot.

Rasa Tools are included in Rasa Pro 3.16 and later. There is no separate package to install.

What are Rasa MCP Tools?

Rasa MCP Tools are Model Context Protocol (MCP) tools that let agentic systems — IDE copilots, browser copilots, and other MCP clients — inspect, validate, train, and debug Rasa agents using natural language.

Building Rasa agents involves business logic spread across flows, slots, custom actions, and configuration files. IDE copilots are strong at coding but lack Rasa-specific knowledge. Rasa MCP Tools bridge that gap by making Rasa a first-class tool provider for your IDE.

What you can do

The MCP server exposes 19 tools across six groups: documentation search, project introspection, schema retrieval, build/validation, runtime testing, and simulation & evaluation. For a complete tool-by-tool reference, see Rasa MCP Tools API Reference.

How it works

Your IDE agent starts rasa tools run, which is the Rasa MCP server: a local process that speaks MCP over stdio and reads your project files directly. You do not need a separate service for most tools. A Rasa Server started with rasa run --inspect is required for the runtime and evaluation tools: talk_to_assistant, get_assistant_logs, and evaluate_agent.

Your machine

┌──────────────┐  MCP (stdio)   ┌──────────────────────┐
  │ IDE Agent    │ ◄────────────► │ Rasa MCP Server      │
  │              │                │ rasa tools run       │
  │ (your IDE)   │                │ reads project files  │
  └──────────────┘                └──────────┬───────────┘
                                             │ optional HTTP
                                             ▼
                                  ┌──────────────────────┐
                                  │ Rasa Server          │
                                  │ rasa run / inspect   │
                                  └──────────────────────┘

Setup

Prerequisites

• Rasa Pro 3.16+ installed ( Python or Docker)
• RASA_LICENSE environment variable set. Some setups (for example Claude Code) start non-interactive shells, so they may not load ~/.zshrc. On zsh, put the license where it is always read, such as ~/.zshenv:

echo 'export RASA_LICENSE="your-license-key"' >> ~/.zshenv

Quick setup with the wizard

Run from your project root:

rasa tools init

The wizard:

• Creates .rasa/tools.yaml with server configuration
• Downloads offline documentation into .rasa/
• Generates MCP configuration for your IDE
• Downloads Rasa specific skills for your project

Use -y to accept all defaults:

rasa tools init -y

After the wizard completes, open your IDE from the project root and check that rasa-tools appears in your IDE's MCP settings.

Manual setup by client

If the wizard did not configure your IDE, or you prefer manual setup, follow the instructions for your client below.

Cursor

1. Open Settings > Tools & MCP and add a new MCP server, or create .cursor/mcp.json in your project root.
2. Add the following config:

.cursor/mcp.json

{
  "mcpServers": {
    "rasa-tools": {
      "command": "rasa",
      "args": ["tools", "run", "--mode", "stdio"]
    }
  }
}

3. Ensure rasa is on your PATH. Restart Cursor or reload MCP.
4. Open your project from the project root.

VS Code (Agent Mode)

1. Create or open .vscode/mcp.json in your project root.
2. Add a server entry:

.vscode/mcp.json

{
  "servers": {
    "rasa-tools": {
      "type": "stdio",
      "command": "rasa",
      "args": ["tools", "run", "--mode", "stdio"]
    }
  }
}

3. Reload the window or restart VS Code. The server will appear in the MCP: List Servers command palette entry.

Claude Code

Claude Code launches non-interactive shells, so it may not inherit your terminal's PATH. Use the full path to rasa.

Option A — CLI (recommended)

From your project root:

claude mcp add rasa-tools -- /path/to/your/.venv/bin/rasa tools run --mode stdio

Option B — edit .mcp.json directly

Create or open .mcp.json in your project root:

.mcp.json

{
  "mcpServers": {
    "rasa-tools": {
      "command": "/path/to/your/.venv/bin/rasa",
      "args": ["tools", "run", "--mode", "stdio"]
    }
  }
}

After either option, run /mcp in Claude Code and confirm rasa-tools is Connected.

JetBrains (IntelliJ, PyCharm, WebStorm, etc.)

1. Open Settings > Tools > AI Assistant > Model Context Protocol (MCP).
2. Click Add and choose STDIO.
3. Enter the following JSON config:

{
  "mcpServers": {
    "rasa-tools": {
      "command": "rasa",
      "args": ["tools", "run", "--mode", "stdio"]
    }
  }
}

Trying it out

After setup, open a copilot chat in your IDE and try these prompts:

Use rasa-tools to summarize what this assistant can do.

Help me use rasa-tools to create a new feature for this project.
Return:
1. User goal
2. Required slots (new vs reused)
3. Happy path
4. Edge cases
5. Test scenarios
Keep it under 15 bullets.

Validate this Rasa project and explain any issues.

Search the Rasa docs for how to add an mcp server to this assistant project.

If the tools respond with project information, your setup is working. See the Prompt-Driven Agent Tutorial for a guided walkthrough of building a feature with prompts.

For runtime testing (talking to the assistant) and simulation-based evaluation, you also need to start the Rasa server:

rasa run --inspect

Then you can test conversations:

Talk to the assistant: "hello", "I want to send money to Jen", "$50", "yes".
Check if the transfer_money flow completed.

See Simulation and Evaluation for the full scenario YAML schema, assertion types, and result file format.

Troubleshooting

For general Rasa Pro installation issues, see Installation Troubleshooting.