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MCP server · Agents

Bonnard

Open-source agentic schema for reliable data outputs. Query data through MCP and via our SDK. Create apps, embed data or just simply explore through your preferred agent.

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Scored 6 months ago · breakdown

About Bonnard

Bonnard is an MCP server in the Agents category: open-source agentic schema for reliable data outputs. Query data through MCP and via our SDK. Create apps, embed data or just simply explore through your preferred agent.

Install

From source
git clone https://github.com/bonnard-data/bonnard

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README


Bonnard is an agent-native semantic layer — one set of metric definitions, every consumer (AI agents, apps, dashboards) gets the same governed answer. This repo is the self-hosted Docker deployment: run Bonnard on your own infrastructure with no cloud account needed.

Quick Start

# 1. Scaffold project
npx @bonnard/cli init --self-hosted

# 2. Configure your data source
#    Edit .env with your database credentials

# 3. Start the server
docker compose up -d

# 4. Define your semantic layer
#    Add cube/view YAML files to bonnard/cubes/ and bonnard/views/

# 5. Deploy models to the server
bon deploy

# 6. Verify your semantic layer
bon schema

# 7. Connect AI agents
bon mcp

Requires Node.js 20+ and Docker.

What's Included

  • MCP server — AI agents query your semantic layer over the Model Context Protocol
  • Cube semantic layer — SQL-based metric definitions with caching, access control, and multi-database support
  • Cube Store — pre-aggregation cache for fast analytical queries
  • Admin UI — browse deployed models, views, and measures at http://localhost:3000
  • Deploy API — push model updates via bon deploy without restarting containers
  • Health endpoint — GET /health for uptime monitoring

Connecting AI Agents

Run bon mcp to see connection config for your setup. Examples below.

Claude Desktop / Cursor

{
  "mcpServers": {
    "bonnard": {
      "url": "https://bonnard.example.com/mcp",
      "headers": {
        "Authorization": "Bearer your-secret-token-here"
      }
    }
  }
}

Claude Code

{
  "mcpServers": {
    "bonnard": {
      "type": "url",
      "url": "https://bonnard.example.com/mcp",
      "headers": {
        "Authorization": "Bearer your-secret-token-here"
      }
    }
  }
}

CrewAI (Python)

from crewai import MCPServerAdapter

mcp = MCPServerAdapter(
    url="https://bonnard.example.com/mcp",
    transport="streamable-http",
    headers={"Authorization": "Bearer your-secret-token-here"}
)

Production Deployment

Authentication

Protect your endpoints by setting ADMIN_TOKEN in .env:

ADMIN_TOKEN=your-secret-token-here

All API and MCP endpoints will require Authorization: Bearer <token>. The /health endpoint remains open for monitoring.

Restart after changing .env:

docker compose up -d

TLS with Caddy

Caddy provides automatic HTTPS via Let's Encrypt.

Create a Caddyfile next to your docker-compose.yml:

bonnard.example.com {
    reverse_proxy localhost:3000
}

Add Caddy to your docker-compose.yml:

  caddy:
    image: caddy:2
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - ./Caddyfile:/etc/caddy/Caddyfile:ro
      - caddy_data:/data
    restart: unless-stopped

Add the volume at the top level:

volumes:
  models: {}
  caddy_data: {}

Then remove the Bonnard port mapping (ports: - "3000:3000") since Caddy handles external traffic.

Deploy to a VM

# Copy project files to your server
scp -r . user@your-server:~/bonnard/

# SSH in and start
ssh user@your-server
cd ~/bonnard
docker compose up -d

Configuration

Variable Description Default
CUBEJS_DB_TYPE Database driver (postgres, duckdb, snowflake, bigquery, databricks, redshift, clickhouse) duckdb
CUBEJS_DB_* Database connection settings (host, port, name, user, pass) —
CUBEJS_DATASOURCES Comma-separated list for multi-datasource setups default
CUBEJS_API_SECRET HS256 secret for Cube JWT auth (auto-generated by bon init) —
ADMIN_TOKEN Bearer token for API/MCP authentication — (open)
CUBE_PORT Cube API port 4000
BONNARD_PORT Bonnard server port 3000
CORS_ORIGIN Allowed CORS origins *
CUBE_VERSION Cube Docker image tag v1.6
BONNARD_VERSION Bonnard Docker image tag latest

See .env.example for a full annotated configuration file.

Architecture

Service Image Role
cube cubejs/cube Semantic layer engine — executes queries against your warehouse
cubestore cubejs/cubestore Pre-aggregation cache — stores materialized results for fast reads
bonnard ghcr.io/bonnard-data/bonnard MCP server, admin UI, deploy API — the interface layer for agents and tools

All three services communicate over an internal Docker network. Only bonnard (port 3000) and optionally cube (port 4000) are exposed externally.

Monitoring

# Health check
curl http://localhost:3000/health

# View logs
docker compose logs -f

# View active MCP sessions
curl -H "Authorization: Bearer <token>" http://localhost:3000/api/mcp/sessions

Deploying Schema Updates

From your development machine:

bon deploy

This pushes your cube/view YAML files to the running server. No restart needed — Cube picks up changes automatically.

Pinning Versions

Control image versions via .env:

CUBE_VERSION=v1.6
BONNARD_VERSION=latest

Supported Data Sources

Warehouses: Snowflake, Google BigQuery, Databricks, PostgreSQL (including Supabase, Neon, RDS), Amazon Redshift, DuckDB (including MotherDuck), ClickHouse

See the full documentation for connection guides.

Ecosystem

  • @bonnard/cli — scaffold projects, deploy models, connect agents
  • @bonnard/sdk — query the semantic layer from JavaScript/TypeScript
  • @bonnard/react — React chart components and dashboard viewer

Community

License

Apache 2.0

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Bonnard

How do I install Bonnard?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Bonnard safe to use with an AI agent?

Its trust score is 39 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Bonnard still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.