Metabase AI Assistant
Provides comprehensive integration with Metabase instances including creating models, SQL queries, metrics, and dashboards through the Metabase API, with AI-powered features for natural language SQL generation and intelligent dashboard creation.
Enables direct PostgreSQL database connections for schema discovery, table relationship detection, SQL query execution, and safe DDL operations with AI object prefix controls for security.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Metabase AI Assistantcreate a dashboard showing monthly sales trends by region"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Metabase AI Assistant — Model Context Protocol (MCP) Server
Metabase AI Assistant is an enterprise-grade Model Context Protocol (MCP) server that connects Large Language Models (LLMs), AI coding assistants, and automated data workflows directly to your Metabase Business Intelligence instance.
Featuring 152 dedicated tools, native dbt Metadata & Metrics Auto-Syncer, Metabase to dbt Reverse Lineage Exposures, dbt-Smart Question Creator, Lightdash Code-as-BI YAML-to-Dashboard generation, Cube.js-style Pre-aggregations & Multi-Hop Lineage Joins, Omni.co Controlled Semantic-to-YAML bridge, autonomous self-healing SQL execution, full-scale dashboard architecting, proactive anomaly detection, query index advisory, zero-leak PII masking, and strict security guardrails. Works seamlessly with Claude, Cursor, ChatGPT, Gemini, and Google Antigravity.
🌍 Language Versions / Dil Seçenekleri / 语言版本 / النسخ اللغوية
Related MCP server: Metabase MCP Server
Table of Contents
Core Architectural Highlights
Metabase AI Assistant transforms standard AI interfaces (Claude Desktop, Cursor, VS Code, ChatGPT, Gemini, automated agent frameworks) into full-fledged Metabase power users:
dbt Deep Scanning & MetricFlow Integration (
dbt_project_scan_deep): 9-tier architectural classification,doc('...')resolution, andcatalog.jsontable/column profiling.Cube.js Multi-Hop Lineage Joins (
dbt_lineage_joins_graph): Resolves shortest join paths via Dijkstra Min-Heap algorithms with 3-color DAG cycle detection.Cube.js Pre-Aggregation & Rollup Advisor (
dbt_semantic_preagg_advisor): Generates multi-dialect Materialized View DDLs (Postgres, BigQuery, Snowflake, ClickHouse, DuckDB, Redshift, MySQL) with HyperLogLog distinct counts.Lightdash Code-as-BI Dashboard Builder (
dbt_build_dashboard_from_yaml): Translatesmeta.metabaseandmeta.lightdashformatting options into collision-free 24-column Metabase Dashboards.Omni.co Controlled Semantic-to-YAML Exporter (
dbt_semantic_export_yaml): Serializes approved business rules into clean dbtschema.yml/semantic_models.ymlcode blocks.Autonomous Self-Healing SQL Engine (
ai_sql_execute_and_heal): 3-iteration automated error-recovery loop for resilient querying.Zero-Leak Enterprise PII Masker: Real-time sanitization of emails, phone numbers, national IDs, credit cards, IP addresses, and tokens.
Next-Gen Autonomous Features (v5.1)
1. dbt Architectural Hierarchy & Source Prioritization
$$\mathbf{Gold;Marts;(fct_,;dim_,;rpt_)} ;\gg; \mathbf{Silver;(int_)} ;\gg; \mathbf{Bronze;Staging;(stg_)}$$
dbt_inspect_models: Parses dbtmanifest.jsonand MetricFlow semantic models.dbt_prioritize_sources: Dynamically routes natural language questions to pre-aggregated, tested dimensional and fact tables.
2. Governance-First Semantic Memory (No Silent Learning, No Hard-Deletes)
semantic_memory_propose: Proposes a business rule inPENDING_APPROVALstatus.semantic_memory_approve: Explicitly activates the rule with required data steward comments.semantic_memory_deprecate: Safely soft-archives rules with mandatory audit reasons (DEPRECATED).semantic_memory_restore: Instantly restores archived rules.semantic_memory_list: Lists all rules with complete audit history and timestamps.
3. Autonomous Self-Healing SQL Engine (ai_sql_execute_and_heal)
Catches syntax errors, Levenshtein-distance column misspellings, missing
GROUP BYclauses, and dialect quirks across Postgres, MySQL, BigQuery, Snowflake, and SQLite.Preserves fix history in
_provenance.healing_trail.
Metabase Version Compatibility
Metabase AI Assistant provides backward and forward compatibility across all major Metabase architectures:
Metabase Version Range | Compatibility Level | Key Features Supported |
Metabase v0.55 – v0.61+ (Current) | Full Support | Modern MBQL 5 format ( |
Metabase v0.50 – v0.54 | Full Support | Collection tree hierarchies ( |
Metabase v0.43 – v0.49 | Full Support | Session token authentication ( |
Metabase Open Source & Enterprise | Full Support | Automatic feature detection (whitelabeling, audit logs, granular data permissions) |
Quick Start & Installation
Global Execution via NPX
npx metabase-ai-assistantManual Installation via NPM
npm install -g metabase-ai-assistantClient Configuration & Desktop Setup
1. Claude Desktop
Option A: One-Click Extension (DXT / MCPB)
Open Claude Desktop Settings -> Developer / Extensions -> Install Local Extension.
Select this repository folder.
Or install via Smithery CLI:
npx -y @smithery/cli install metabase-ai-assistant --client claude
Option B: Manual JSON Configuration
Add the server definition to claude_desktop_config.json:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"metabase": {
"command": "npx",
"args": ["-y", "metabase-ai-assistant"],
"env": {
"METABASE_URL": "https://your-metabase-instance.com",
"METABASE_API_KEY": "mb_your_api_key_here",
"METABASE_READ_ONLY_MODE": "true"
}
}
}
}2. Cursor IDE, Windsurf & VS Code
Add to .cursor/mcp.json or VS Code MCP settings:
{
"mcpServers": {
"metabase": {
"command": "npx",
"args": ["-y", "metabase-ai-assistant"],
"env": {
"METABASE_URL": "https://your-metabase-instance.com",
"METABASE_API_KEY": "mb_your_api_key_here",
"METABASE_READ_ONLY_MODE": "true"
}
}
}
}3. ChatGPT Custom GPTs & Actions
Expose Metabase AI Assistant as an OpenAPI Action for ChatGPT Plus / Team / Enterprise:
Start the Remote SSE/HTTP server:
npm run start:sseIn ChatGPT, create a Custom GPT -> Actions -> Import from URL:
https://your-domain.com/tools/openapi.jsonDetailed setup guide: docs/integrations/CHATGPT_ACTIONS_GUIDE.md
4. Google Gemini & Google AI Studio
Pass tool definitions to Gemini Function Calling SDKs (@google/genai or google-generativeai):
Detailed setup guide: docs/integrations/GOOGLE_GEMINI_GUIDE.md
5. Cloudflare Workers (Serverless Edge)
Deploy directly to Cloudflare's edge network for free:
cd deploy/cloudflare
npx wrangler deployTool Categories Overview (143 Tools)
The 143 MCP tools are categorized into 10 operational domains:
dbt & Semantic Layer (6 tools): Model hierarchy inspection, lineage resolution, source prioritization, governance-first business memory (propose, approve, soft-deprecate, restore).
Autonomous AI BI Operations (4 tools): Self-healing SQL engine, end-to-end dashboard architect, query index advisor, proactive anomaly detector.
SQL & Query Execution (14 tools): Direct SQL queries, async execution jobs, query status tracking, pagination, and speed benchmarks.
AI Query Intelligence (6 tools): Natural language to SQL, query performance optimizer, query explainer, automated table description.
Cards & Visualizations (34 tools): Question creation, query execution, parametric filtering, card cloning, visualization settings.
Dashboards & Layouts (22 tools): Dashboard creation, grid placement, filter linking, tab management, executive templates.
Collections & Organization (8 tools): Collection tree traversal, hierarchical moves, permission graphs, item listing.
Schema & Data Modeling (18 tools): Schema retrieval, foreign key inference, data profiling, table definitions.
User & Permission Administration (12 tools): User invitations, group assignments, membership controls, status toggling.
Actions & Documentation (19 tools): Metabase actions execution, pulses, alerts, webhooks, metrics, segment definitions, workspace migration.
Testing & Quality Assurance
Backed by an automated multi-tier test suite covering unit logic, integration workflows, and security fuzzing:
# Run complete test suite (32 suites, 583 tests)
npm test
# Run unit tests
npm run test:unit
# Run integration workflows
npm run test:integration
# Run security & PII zero-leak fuzzing tests
npm run test:securityLicense
Licensed under the Apache License 2.0. See the LICENSE file for details.
Developed and maintained by Abdullah Enes SARI (ONMARTECH LLC).
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