Metabase MCP Server ★★★ Official

Source: mcpservers.org · Last updated: July 27, 2026 (early morning sweep)
GitHub: metabase/metabase ⭐ 48,400+
Endpoint: https://<your-metabase-instance>/api/mcp (Streamable HTTP, built-in)
Auth: Metabase API key or session token
Category: Business Intelligence / Data & Analytics

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Overview

Metabase ships a built-in MCP server starting from its July 2026 release. AI clients connect directly to your Metabase instance and use the semantic layer to search, query, and visualize data - no separate connector required. It builds on Metabase's Agent API to expose tools for navigating your entire BI surface area: databases, tables, questions, dashboards, and collections.

This is the first major BI platform to ship MCP natively - a paradigm shift for how operators interact with business data.

Key Capabilities

• Search - Find tables, metrics, cards, dashboards, and collections using keywords or natural-language queries
• Navigate entities - Read metadata for databases, schemas, tables, questions, dashboards, and metrics via metabase:// URIs
• Build and run queries - Construct queries against tables or metrics, execute them, and get structured results with column metadata
• Run raw SQL - Execute native SQL against databases (requires native-query permission)
• Save and update questions - Create or modify saved questions (cards) from agent-constructed queries
• Dashboard management - Create new dashboards with auto-positioned saved questions, update metadata, archive

Tools Reference

Tool	Description
search	Search Metabase content by keyword/query
read_resource	Read entity metadata using metabase:// URIs
construct_query	Build a query against a table or metric
execute_query	Execute a constructed query and return results
execute_sql	Run native SQL (requires permissions)
create_question	Save a query as a question/card
update_question	Modify an existing question, including archiving
create_dashboard	Build a new dashboard with auto-positioned cards
update_dashboard	Modify dashboard metadata or archive

Integration

Prerequisites

• Metabase instance (self-hosted or Metabase Cloud) running the July 2026+ release
• API key with appropriate permissions (Admin > Settings > Authentication > API Keys)

1. Claude Desktop

{
  "mcpServers": {
    "metabase": {
      "type": "http",
      "url": "https://metabase.yourcompany.com/api/mcp",
      "headers": {
        "x-api-key": "mb_YOUR_API_KEY"
      }
    }
  }
}

2. Hermes Agent (config.yaml)

mcp:
  servers:
    metabase:
      type: http
      url: https://metabase.yourcompany.com/api/mcp
      headers:
        x-api-key: ${METABASE_API_KEY}

3. Cursor / VS Code

Connect via Streamable HTTP at https://metabase.yourcompany.com/api/mcp with the x-api-key header.

Business Operator Use Cases

1. Natural Language Analytics - "What was our MRR last month broken down by plan tier?" - agent queries Metabase and returns formatted results
2. Automated Board Reports - Agent pulls KPIs from Metabase dashboards weekly, formats into a report
3. Anomaly Detection - Agent monitors key metrics and alerts on unexpected deviations
4. Ad-Hoc Data Exploration - "Show me churn by acquisition channel for Q2" - agent builds and executes the query
5. Dashboard Creation - Agent auto-builds dashboards for new initiatives based on natural language descriptions

Pricing

• Metabase MCP server: Free (included with Metabase)
• Metabase Open Source: Free (self-hosted)
• Metabase Cloud: Starter at $85/month (includes MCP support)

Security Considerations

• API key scoped to specific Metabase permissions
• Native SQL execution requires explicit permission (disabled by default)
• All queries respect Metabase's existing data sandboxing and row-level permissions
• ⚠️ Write operations (create/update questions and dashboards) should be tested in a staging instance first

Verdict

★★★★★ - The first major BI platform to go MCP-native. Essential for any business operator running Metabase who wants AI agents to interact with their BI layer directly. The built-in semantic layer means agents query meaningful business concepts ("MRR", "churn"), not raw table names - this is the right architecture for AI-powered analytics.

Integration with CorpusIQ

CorpusIQ is the connector layer that lets AI assistants read the systems a business already runs on - accounting, payments, CRM, email, files and analytics - and answer with the source named. It is read-only by design: it retrieves data and never writes to, or acts in, a connected system, which is what makes it safe to point at live accounts.

This page is part of the CorpusIQ directory, the reference we maintain for the MCP server and agent-skill ecosystem. Run alongside CorpusIQ, a third-party server like this one can be combined with a company's own business data in a single answer.

See what CorpusIQ connects