io.github.enessari/metabase-ai-assistant

AI 与智能体

by enessari

面向 Metabase 的 MCP Server,提供 111 项工具,支持 SQL 生成、仪表板构建与 PostgreSQL 操作。

什么是 io.github.enessari/metabase-ai-assistant

面向 Metabase 的 MCP Server,提供 111 项工具,支持 SQL 生成、仪表板构建与 PostgreSQL 操作。

README

Metabase AI Assistant — Model Context Protocol (MCP) Server

npm version License Node.js MCP SDK

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


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:

  1. dbt Deep Scanning & MetricFlow Integration (dbt_project_scan_deep): 9-tier architectural classification, doc('...') resolution, and catalog.json table/column profiling.
  2. 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.
  3. 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.
  4. Lightdash Code-as-BI Dashboard Builder (dbt_build_dashboard_from_yaml): Translates meta.metabase and meta.lightdash formatting options into collision-free 24-column Metabase Dashboards.
  5. Omni.co Controlled Semantic-to-YAML Exporter (dbt_semantic_export_yaml): Serializes approved business rules into clean dbt schema.yml / semantic_models.yml code blocks.
  6. Autonomous Self-Healing SQL Engine (ai_sql_execute_and_heal): 3-iteration automated error-recovery loop for resilient querying.
  7. 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 dbt manifest.json and 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 in PENDING_APPROVAL status.
  • 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 BY clauses, 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 RangeCompatibility LevelKey Features Supported
Metabase v0.55 – v0.61+ (Current)Full SupportModern MBQL 5 format (stages, lib/type), /api/upload/csv, updated collection permissions, multi-tab dashboards
Metabase v0.50 – v0.54Full SupportCollection tree hierarchies (/api/collection/tree), Model cards, API Key auth (x-api-key), sequential parametric queries
Metabase v0.43 – v0.49Full SupportSession token authentication (X-Metabase-Session), legacy MBQL query pipelines, database introspection
Metabase Open Source & EnterpriseFull SupportAutomatic feature detection (whitelabeling, audit logs, granular data permissions)

Quick Start & Installation

Global Execution via NPX

bash
npx metabase-ai-assistant

Manual Installation via NPM

bash
npm install -g metabase-ai-assistant

Client Configuration & Desktop Setup

1. Claude Desktop

Option A: One-Click Extension (DXT / MCPB)

  1. Open Claude Desktop Settings -> Developer / Extensions -> Install Local Extension.
  2. Select this repository folder.
  3. Or install via Smithery CLI:
    bash
    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.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
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:

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"
      }
    }
  }
}

3. ChatGPT Custom GPTs & Actions

Expose Metabase AI Assistant as an OpenAPI Action for ChatGPT Plus / Team / Enterprise:

  1. Start the Remote SSE/HTTP server: npm run start:sse
  2. In ChatGPT, create a Custom GPT -> Actions -> Import from URL: https://your-domain.com/tools/openapi.json
  3. Detailed 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):

5. Cloudflare Workers (Serverless Edge)

Deploy directly to Cloudflare's edge network for free:

bash
cd deploy/cloudflare
npx wrangler deploy

Tool Categories Overview (143 Tools)

The 143 MCP tools are categorized into 10 operational domains:

  1. dbt & Semantic Layer (6 tools): Model hierarchy inspection, lineage resolution, source prioritization, governance-first business memory (propose, approve, soft-deprecate, restore).
  2. Autonomous AI BI Operations (4 tools): Self-healing SQL engine, end-to-end dashboard architect, query index advisor, proactive anomaly detector.
  3. SQL & Query Execution (14 tools): Direct SQL queries, async execution jobs, query status tracking, pagination, and speed benchmarks.
  4. AI Query Intelligence (6 tools): Natural language to SQL, query performance optimizer, query explainer, automated table description.
  5. Cards & Visualizations (34 tools): Question creation, query execution, parametric filtering, card cloning, visualization settings.
  6. Dashboards & Layouts (22 tools): Dashboard creation, grid placement, filter linking, tab management, executive templates.
  7. Collections & Organization (8 tools): Collection tree traversal, hierarchical moves, permission graphs, item listing.
  8. Schema & Data Modeling (18 tools): Schema retrieval, foreign key inference, data profiling, table definitions.
  9. User & Permission Administration (12 tools): User invitations, group assignments, membership controls, status toggling.
  10. 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:

bash
# 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:security

License

Licensed under the Apache License 2.0. See the LICENSE file for details.

Developed and maintained by Abdullah Enes SARI (ONMARTECH LLC).

常见问题

io.github.enessari/metabase-ai-assistant 是什么?

面向 Metabase 的 MCP Server,提供 111 项工具,支持 SQL 生成、仪表板构建与 PostgreSQL 操作。

相关 Skills

Claude接口

by anthropics

Universal
热门

面向接入 Claude API、Anthropic SDK 或 Agent SDK 的开发场景,自动识别项目语言并给出对应示例与默认配置,快速搭建 LLM 应用。

想把Claude能力接进应用或智能体,用claude-api上手快、兼容Anthropic与Agent SDK,集成路径清晰又省心

AI 与智能体
未扫描175.1k

多智能体架构

by alirezarezvani

Universal
热门

聚焦多智能体系统架构设计,梳理 Supervisor、Swarm、分层和 Pipeline 等模式,覆盖角色定义、通信协作与性能评估,适合规划稳健可扩展的 AI agent 编排方案。

帮你系统解决多智能体应用的架构设计与协同编排难题,适合构建复杂 AI 工作流,成熟度高、社区认可也很亮眼。

AI 与智能体
未扫描25.7k

RAG架构师

by alirezarezvani

Universal
热门

聚焦生产级RAG系统设计与优化,覆盖文档切块、检索链路、索引构建、召回评估等关键环节,适合搭建可扩展、高准确率的知识库问答与检索增强应用。

面向RAG落地,把知识库、向量检索和生成链路系统串联起来,做架构设计时更清晰,也更少踩坑。

AI 与智能体
未扫描25.7k

相关 MCP Server

知识图谱记忆

编辑精选

by Anthropic

热门

Memory 是一个基于本地知识图谱的持久化记忆系统,让 AI 记住长期上下文。

帮 AI 和智能体补上“记不住”的短板,用本地知识图谱沉淀长期上下文,连续对话更聪明,数据也更可控。

AI 与智能体
89.7k

顺序思维

编辑精选

by Anthropic

热门

Sequential Thinking 是让 AI 通过动态思维链解决复杂问题的参考服务器。

这个服务器展示了如何让 Claude 像人类一样逐步推理,适合开发者学习 MCP 的思维链实现。但注意它只是个参考示例,别指望直接用在生产环境里。

AI 与智能体
89.2k

by deusdata

热门

持久化的代码库知识图谱,可跨会话保留上下文,在 session 重启或上下文压缩后仍能继续使用。

专治 AI 编程助手“会话失忆”,把代码库沉淀为持久知识图谱,重启或压缩上下文后也能无缝续上开发状态。

AI 与智能体
37.3k

评论