Give AI tools like Cursor, VS Code, and Claude Desktop access to your company's product knowledge through the Biel.ai platform.
Biel.ai provides a hosted Retrieval-Augmented Generation (RAG) layer that makes your documentation searchable and useful to AI tools. This enables smarter completions, accurate technical answers, and context-aware suggestions—directly in your IDE or chat environment.
When AI tools can read your product documentation, they become significantly more helpful—generating more accurate code completions, answering technical questions with context, and guiding developers with real-time product knowledge.
Note: Requires a Biel.ai account and project setup. Start your free 15-day trial.
{
"mcpServers": {
"biel-ai": {
"description": "Query your product's documentation, APIs, and knowledge base.",
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.biel.ai/sse?project_slug=YOUR_PROJECT_SLUG&domain=https://your-docs-domain.com"
]
}
}
}Required: project_slug and domain
Optional: api_key (only needed for private projects)
- Cursor: Settings → *Tools & Integrations → New MCP server.
- Claude Desktop: Edit
claude_desktop_config.json - VS Code: Install MCP extension.
Can you check in biel_ai what the auth headers are for the /users endpoint?
The server exposes three tools:
biel_ai: ask Biel.ai to generate an answer, with conversational context. Existing calls usingmessagecontinue to generate answers.biel_search: hybrid keyword and semantic search over indexed web pages, uploaded files, repositories and OpenAPI sources, without answer generation.biel_get_document: read the complete indexed text of a document returned by search.
Call biel_search with a natural-language question or search terms:
{"query": "How do I authenticate with the SDK?", "limit": 5}Search requests the API's search_type=hybrid&source_types=all. The REST API defaults to search_type=keyword, independently of the selected sources. Results include chunk text, source type, a document_id, and any page/sheet reference; non-URL documents are cited by title and location. The limit argument controls how many chunks are returned (default 5, maximum 20).
Use biel_get_document with a search result's document_id to read the complete indexed document without visiting its source site:
{"document_id": "DOCUMENT_ID_FROM_SEARCH", "limit": 20}Get returns full indexed chunks in reading order, with PDF page and spreadsheet sheet references. Large documents include a next_cursor; repeat the call with that cursor and the same document_id and limit until it is absent. This returns the indexed text, not the original binary upload or live page HTML. References belong to the project's active index generation: search again after a recrawl invalidates a reference. Older repository and OpenAPI sources require a recrawl to populate parent-document identity before get is available.
Search and get do not create or continue a chat. Private projects require an API key with the search scope; generated answers use chats_create. All operations retain the API's project access, domain and quota checks. The default workflow is search → get → answer using the retrieved text. If the calling agent wants Biel.ai to generate an answer, it should ask the user first unless the user has already explicitly requested that. Retrieval failures never automatically switch to generated answers.
For advanced users who prefer to run their own MCP server instance:
# Clone and run locally
git clone https://github.com/TechDocsStudio/biel-mcp
cd biel-mcp
pip install .
biel-mcpApplications that host their own ASGI stack can install the server directly from a tagged revision and import its FastAPI application:
pip install "biel-mcp @ git+https://github.com/TechDocsStudio/biel-mcp.git@VERSION"from biel_mcp.server import app# Docker Compose (recommended)
docker-compose up -d --build
# Or Docker directly
docker build -t biel-mcp .
docker run -d -p 7832:7832 biel-mcp- Issues: GitHub Issues
- Contact: support@biel.ai
- Custom Demo: Book a demo