> ## Documentation Index > Fetch the complete documentation index at: https://rasa.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # Rasa MCP Tools > Learn about and configure the Rasa MCP server for Cursor, VS Code, Claude Code, and JetBrains clients. **Rasa Tools are included in Rasa Pro 3.16 and later.** There is no separate package to install. v3.16 ## What are Rasa MCP Tools? Rasa MCP Tools are [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) 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](/docs/learn/concepts/calm), [slots](/docs/reference/primitives/slots), [custom actions](/docs/learn/guides/adding-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 | Capability | Example prompt | | ------------ | ---------------------------------------------------------------------------- | | **Inspect** | "What flows and slots are in this project?" | | **Build** | "Help me add a new subagent that manages flight bookings." | | **Validate** | "Validate my project and explain any errors." | | **Train** | "Train the model and tell me if it succeeded." | | **Test** | "Send 'I want to transfer money' to the assistant and show me what happens." | | **Evaluate** | "Generate and run scenarios for the add\_contact flow." | | **Debug** | "Get the assistant logs and explain why the flow was cancelled." | | **Learn** | "Search the Rasa docs for how slot validation works." | 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](/docs/reference/api/rasa-mcp-tools). ### 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](/docs/pro/installation/python) or [Docker](/docs/pro/installation/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`: ```bash theme={null} echo 'export RASA_LICENSE="your-license-key"' >> ~/.zshenv ``` ### Quick setup with the wizard Run from your **project root**: ```bash theme={null} 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. Each skill installs as `/SKILL.md` in your IDE's skills directory, along with any supporting files from the skill's `references/` folder. Use `-y` to accept all defaults: ```bash theme={null} 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. Configure Rasa MCP Tools in Cursor. Configure Rasa MCP Tools in Visual Studio Code. Configure Rasa MCP Tools in Claude Code. Configure Rasa MCP Tools in a JetBrains IDE. Your IDE starts the Rasa Tools process and communicates over **stdio**. Add a server entry like the examples below. Use the same `rasa` binary you use in a terminal where `rasa train` works. Always run from the **project root** unless you pass an explicit `--project-path`. If your IDE does not inherit `RASA_LICENSE` from your shell (common when launching from Dock or Spotlight instead of a terminal), add it via the `env` field in your MCP config: ```json theme={null} "env": { "RASA_LICENSE": "your-license-key" } ``` ### 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: ```json title=".cursor/mcp.json" theme={null} { "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: ```json title=".vscode/mcp.json" theme={null} { "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` (run `which rasa` inside your activated virtualenv to find it). **Option A — CLI (recommended)** From your **project root**: ```bash theme={null} claude mcp add rasa-tools -- /path/to/your/.venv/bin/rasa tools run --mode stdio ``` This writes the entry to `~/.claude.json`. To store it in the project (shareable via git), add `-s project`: ```bash theme={null} claude mcp add -s project 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: ```json title=".mcp.json" theme={null} { "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: ```json theme={null} { "mcpServers": { "rasa-tools": { "command": "rasa", "args": ["tools", "run", "--mode", "stdio"] } } } ``` 4. Set the **Working directory** to your Rasa project root. 5. Click **OK** and restart the AI Assistant. **Using a virtualenv interpreter** If `rasa` is not on the global `PATH`, point `command` at your venv Python and run Rasa as a module: ```json theme={null} { "mcpServers": { "rasa-tools": { "command": "/path/to/project/.venv/bin/python", "args": [ "-m", "rasa", "tools", "run", "--mode", "stdio", "--project-path", "/path/to/rasa/project" ], "env": { "RASA_LICENSE": "your_license_key_here" } } } } ``` Remove `--project-path` if you always start the IDE from the project root. ## Trying it out After setup, open a copilot chat in your IDE and try these prompts: ```text theme={null} Use rasa-tools to summarize what this assistant can do. ``` ```text theme={null} 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. ``` ```text theme={null} Validate this Rasa project and explain any issues. ``` ```text theme={null} 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](/docs/learn/ai-assisted-development) 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: ```bash theme={null} rasa run --inspect ``` Then you can test conversations: ```text theme={null} Talk to the assistant: "hello", "I want to send money to Jen", "$50", "yes". Check if the transfer_money flow completed. ``` Or run a simulation evaluation: ```text theme={null} Generate and run a happy path scenario for the add_contact flow. ``` ```text theme={null} Run all scenarios in eval/scenarios/ and give me a summary of what failed. ``` See [Simulation and Evaluation](/docs/reference/testing/evals/overview) for the full scenario YAML schema, assertion types, and result file format. ## Troubleshooting | Issue | What to do | | ------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | IDE says "no MCP servers found" | Check that the MCP config file exists in the right location and the JSON is valid. Cursor: `.cursor/mcp.json`. VS Code: `.vscode/mcp.json`. Claude Code: `.mcp.json` or `~/.claude.json`. Reload or restart MCP in your IDE. | | `rasa: command not found` | Ensure `rasa` is on your `PATH`. If using a virtualenv, use the full path to `rasa` (find it with `which rasa`), or point `command` at `.venv/bin/python` and use `-m rasa` in `args`. See [JetBrains example](/docs/pro/installation/rasa-mcp-tools#jetbrains). | | `RASA_LICENSE` not found / license error | The IDE may not inherit your shell environment. Add `"env": { "RASA_LICENSE": "..." }` to your MCP server config, or for zsh put the export in `~/.zshenv` (not only `~/.zshrc`). See [Prerequisites](/docs/pro/installation/rasa-mcp-tools#prerequisites). | | Claude Code: `rasa-tools` not connected (`/mcp`) | Use the full path to `rasa` from `which rasa` in your venv. Confirm `RASA_LICENSE` is set (see row above). Verify **Rasa Pro 3.16+** with `rasa --version`. See [Claude Code](/docs/pro/installation/rasa-mcp-tools#claude-code). | | "Project folder not configured" | Run from the project root, or add `--project-path` to your MCP args. | | Tools work but `talk_to_assistant` fails | Start the Rasa server first: `rasa run` or `rasa run --inspect`. The MCP server connects to `http://localhost:5005` by default. | | Offline docs are stale | Run `rasa tools init docs` and restart the MCP server. | | First tool call is slow | Expected. The MCP server lazy-loads Rasa modules on first use. Subsequent calls are faster. | | Validation/training hangs | Large projects can take 60+ seconds. If it truly hangs, check terminal for errors. | | Server connects but no tools appear | Restart the MCP server from your IDE. In Cursor: toggle the server off/on in Settings. In VS Code: run **MCP: List Servers** and restart. In Claude Code: `/mcp` then restart. | | `evaluate_agent` fails to fetch tracker | The eval tool requires the Rasa REST API. Start your server with `rasa run --inspect`. The `--inspect` flag enables the REST API automatically. You do not need `--enable-api` separately. | | Stale MCP config — `/clear` or new thread doesn't fix it | The MCP server process itself is stale. Restart it from your IDE (see "Server connects but no tools appear" above), then verify `evaluate_agent` is listed before retrying. | | `rasa-simulating-conversations` skill not loading | Open your IDE from the **root directory of your assistant project**. Skills are scoped to the project root and will not load if you open a parent or unrelated directory. | | Skills list is empty or `rasa-simulating-conversations` is missing | Run `rasa tools init` from your project root and select "Install Rasa agent skills" when prompted. Restart your IDE afterward. | For general Rasa Pro installation issues, see [Installation Troubleshooting](/docs/pro/installation/troubleshooting). ## Related * [Rasa MCP Tools API Reference](/docs/reference/api/rasa-mcp-tools) — full tool-by-tool reference with parameters and sample prompts * [Simulation and Evaluation](/docs/reference/testing/evals/overview) — scenario YAML schema, assertion types, conftest configuration, and result file formats * [Developer Quickstart](/docs/learn/quickstart/pro) — fastest path to a working project * [Prompt-Driven Agent Tutorial](/docs/learn/ai-assisted-development) — build your first feature with prompts ## Related topics - [Get Started with Rasa](/docs/pro/installation/overview.md) - [Rasa MCP Tools API Reference](/docs/reference/api/rasa-mcp-tools.md) - [Developer Quickstart](/docs/learn/quickstart/pro.md) - [Simulating and Evaluating Your Agent](/docs/pro/testing/simulation-evaluation.md) - [Build an Agent with Prompts](/docs/learn/ai-assisted-development.md)