# N8n MCP RAG

> This tool generates importable n8n workflows from plain English descriptions

- **Type:** MCP server
- **Install:** `agentstack add mcp-christinec-dev-n8n-mcp-rag`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [christinec-dev](https://agentstack.voostack.com/s/christinec-dev)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [christinec-dev](https://github.com/christinec-dev)
- **Source:** https://github.com/christinec-dev/n8n-MCP-RAG
- **Website:** https://n8n-rag-app.duckdns.org/ui

## Install

```sh
agentstack add mcp-christinec-dev-n8n-mcp-rag
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# n8n Workflow Builder (RAG)

This tool generates importable n8n workflows from plain English descriptions, using Retrieval-Augmented Generation (RAG) to reduce hallucinations and match your style. It supports OpenAI, Anthropic, Google Gemini, and Ollama/LM Studio via OpenAI-compatible endpoints.

**Now with [LangWatch](https://langwatch.ai/) integration for monitoring RAG performance!**

**✨ New Features (2025):**
- **Prompt Refinement Button:** Instantly rewrite and clarify your workflow prompt using AI best practices—just click "Refine Prompt" in the UI.
- **Flexible Prompt Input:** Enter either plain English or structured JSON (with fields like `goal`, `triggers`, `integrations`, etc.) for more control.
- **Automatic Prompt Rewriting:** Short or ambiguous prompts are automatically expanded by the AI for better workflow generation.
- **Distributed Caching:** Fast repeated generations and retrievals, even across multiple servers, using Redis (or in-memory fallback).

## Key Features
- **RAG Implementation**: Retrieves relevant chunks from indexed docs/workflows before generating.
- **FastAPI Backend**: Handles API requests, retrieval, prompt building, model calling, and LangWatch logging.
- **LangWatch Monitoring**: Automatically logs RAG requests and responses to LangWatch for observability and performance tracking.
- **Static UI**: Simple web interface at `/ui` for user interaction.
- **Flexible Storage**: Uses local Chroma DB or Chroma Cloud for vector storage.
- **Provider Support**: OpenAI, Anthropic, Gemini, and OpenAI-compatible endpoints.

## Example:

## Project Structure
```
.
├─ mcp_server.py          # FastAPI app (endpoints, retrieval, prompt building, model calling, LangWatch logging)
├─ chunk_all.py           # Splits docs/workflows into JSON chunks
├─ build_chroma.py        # Embeds chunks into local Chroma DB
├─ build_chroma_cloud.py  # Embeds chunks into Chroma Cloud (optional)
├─ ui/                    # Static UI files (served at /ui)
├─ data/                  # Directory for chunked data
│  └─ chunks/             # Contains generated chunks
├─ chroma_db/             # Local Chroma DB (not checked in)
├─ Dockerfile
├─ docker-compose.yml
└─ .env                   # Configuration file (not committed)
```

## Requirements
- Docker and Docker Compose
- API key for one of the supported providers (e.g., OpenAI, Anthropic, etc.)
- (Optional) A Chroma Cloud account/token if you prefer cloud indexing.
- (Optional) [LangWatch](https://langwatch.ai/) API key for RAG monitoring

## Configuration
Create a `.env` file in the project root with your settings. Example configurations:

### A) OpenAI Provider
```env
PROVIDER=openai
OPENAI_MODEL=gpt-4o-mini
OPENAI_API_KEY=your-api-key  # Or leave empty to input via UI
```

### B) Ollama Provider
```env
PROVIDER=openai
OPENAI_MODEL=llama3.1:8b
OPENAI_BASE_URL=http://host.docker.internal:11434/v1
OPENAI_API_KEY=ollama  # Dummy key for Ollama compatibility
```

### C) Local Chroma DB
If using local Chroma, set:
```env
RUN_INDEX_ON_START=false
```

### D) LangWatch Integration
To enable LangWatch monitoring, add your LangWatch API key:
```env
LANGWATCH_API_KEY=your-langwatch-api-key
```

## Running the Project
### Using Docker
1. Build and start the container:
   ```bash
   docker compose up -d --build
   docker compose logs -f app
   ```
   The app runs on `http://localhost:8000` by default.

2. Access the UI (the actual app) at `http://localhost:8000/ui`.

### Indexing Your Data
- **One-Time Local Indexing**:
  ```bash
  docker compose run --rm app python chunk_all.py
  docker compose run --rm app python build_chroma.py
  ```

- **Reindex on Demand**:
  ```bash
  curl -X POST "http://localhost:8000/reindex" -H "X-Admin-Token: your-admin-token"
  ```

## Using the Application
- **UI Interaction**:
  - Describe your workflow in plain English, or use structured JSON for advanced control.
  - Use the **Refine Prompt** button to rewrite your prompt for clarity and best practices before generating.
  - Select a provider and model, then generate the workflow JSON.
- **Prompt Flexibility**:
  - Supports both freeform text and structured JSON input (e.g., `{ "goal": "...", "triggers": ["..."], "integrations": ["..."] }`).
  - Short or vague prompts are automatically rewritten by the AI for better results.
- **Endpoints**:
  - `GET /health`: Check server status.
  - `GET /search?q=...`: Retrieve context snippets (for debugging).
  - `POST /generate`: Submit a prompt and get the generated workflow JSON.
  - `POST /ui_generate`: Same as `/generate` but accepts provider/model/API key headers.
  - `POST /refine_prompt`: Refine/rewrite a prompt using the same AI logic as the UI button.

## LangWatch Monitoring
- When `LANGWATCH_API_KEY` is set, all RAG requests and responses are automatically logged to LangWatch.
- Use the [LangWatch dashboard](https://app.langwatch.ai/) to monitor, analyze, and improve your RAG pipeline.

## Troubleshooting
- **Prompt Not Improving?**: Use the Refine Prompt button to rewrite your input, or try structured JSON for more control.
- **Model Errors**: Use a stronger model (e.g., `gpt-4o` or `claude-3-5-sonnet`) or clarify your prompt.
- **Indexing Issues**: Ensure your Chroma token and settings are correct. Stop the container and rebuild if needed.
- **Docker Problems**: Verify Docker is running and network settings are correct.
- **LangWatch Issues**: Check your `LANGWATCH_API_KEY` and network connectivity.
- **Cache Not Working?**: Make sure Redis is running and `REDIS_URL` is set, or fallback to in-memory cache.

## Security Notes
- API keys are sent per request via headers and not stored on the server.
- Protect sensitive endpoints with strong tokens and consider using a reverse proxy for production.

## License
MIT 

## Quick Start
1. Clone the repository and copy the `.env.example` to `.env`.
2. (Optional) Run indexing:
   ```bash
   docker compose run --rm app python chunk_all.py
   docker compose run --rm app python build_chroma.py
   ```
3. Start the app:
   ```bash
   docker compose up -d --build
   docker compose logs -f app
   ```

4. Open `http://localhost:8000/ui` and start generating workflows!

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [christinec-dev](https://github.com/christinec-dev)
- **Source:** [christinec-dev/n8n-MCP-RAG](https://github.com/christinec-dev/n8n-MCP-RAG)
- **License:** MIT
- **Homepage:** https://n8n-rag-app.duckdns.org/ui

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** yes
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-christinec-dev-n8n-mcp-rag
- Seller: https://agentstack.voostack.com/s/christinec-dev
- Browse the marketplace: https://agentstack.voostack.com/browse

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