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Biel.ai

Biel.ai

Remote
biel.aiAI & Agents3Updated 6d ago

About Biel.ai

Biel.ai turns indexed technical documentation into searchable context and sourced answers for AI assistants and agents. It supports hybrid search, full-document retrieval, and optional answer generation through a project-specific MCP server.

Key features

  1. 01Hybrid keyword and semantic search
  2. 02Retrieve full indexed documents
  3. 03Generate answers with conversational context
  4. 04Results include source references
  5. 05Supports web pages, files, repositories, and OpenAPI sources

Use cases

  1. 01Finding API authentication instructions
  2. 02Grounding coding-agent answers in project docs
  3. 03Reading complete documents returned by search

MCP support

The project-specific MCP server exposes `biel_search`, `biel_get_document`, and `biel_ai` to compatible clients. Search retrieves indexed content, document retrieval returns full text, and `biel_ai` generates an answer when requested.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://mcp.biel.ai/v2/{project_slug}/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://mcp.biel.ai/v2/{project_slug}/mcp
SSEhttps://mcp.biel.ai/sse?project_slug={project_slug}&domain={domain}

Tools

1
ParameterTypeRequiredDescription
messagestringYesYour question about code, SDK or documentation
api_keystringNoAPI key for authentication (optional)
chat_uuidstringNoChat UUID to continue conversation (optional)
domainstringNoDomain URL. Required only if 'Allowed domains' is enabled in project settings.
metadatastringNoMetadata to tag the conversation source (optional)

Details

From the project README
Biel.ai

Biel.ai MCP Server

Give AI assistants context from technical documentation

Biel.ai turns technical documentation into answers for users and context for AI agents, with links back to the sources. This MCP server connects Claude Code, Codex, Cursor, and other compatible clients to documentation indexed in a Biel.ai project.

The usual workflow is to search for relevant content, retrieve indexed documents when more context is needed, and answer in the calling AI assistant. Biel.ai can also generate an answer when you explicitly request one. Source grounding does not eliminate model error; check the retrieved content and references.

Demo

Requires a Biel.ai account, indexed sources, and hosted MCP enabled on a plan that includes it. Create an account and follow the MCP setup guide.

Getting started

1. Enable MCP and copy your endpoint

Open your project in Biel.ai, go to Settings > MCP, enable the MCP server, and save. Copy the complete endpoint supplied for your project.

2. Connect your AI client

Use the canonical documentation for client-specific steps:

The example configuration uses mcp-remote as a bridge for clients without native Streamable HTTP support. Clients with native HTTP support should connect directly using their own configuration format.

3. Verify retrieval

Confirm the client discovers biel_search, biel_get_document, and biel_ai. Ask a question your indexed documentation covers:

Use biel_search to find our API authentication instructions. Read relevant
results with biel_get_document and explain the required headers with source links.

Check the retrieved text and citations against the documentation. MCP serves indexed content; refresh sources in Biel.ai after documentation changes and search again for current document IDs.

Choose generated answers or search

The server exposes three tools:

  • biel_ai: ask Biel.ai to generate an answer, with conversational context. Existing calls using message continue 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}

Troubleshooting

Public projects do not need an API key. Private projects require an api_key query parameter with search permission for retrieval and chats_create for generated answers.

A domain query parameter is needed when allowed domains are configured. See connection parameters before connecting a private or domain-restricted project. Treat a URL containing a key as a credential and keep it out of shared configuration.

Self-hosting (Optional)

For advanced users who prefer to run their own MCP server instance:

Local development
# Clone and run locally
git clone https://github.com/TechDocsStudio/biel-mcp
cd biel-mcp
pip install .
biel-mcp
Use as a Python package

Applications 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 deployment
# Docker Compose (recommended)
docker-compose up -d --build

# Or Docker directly
docker build -t biel-mcp .
docker run -d -p 7832:7832 biel-mcp

Support

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.