"A tool to query data in Metabase and ask questions" matching MCP servers:

Enables AI models to ask users questions through a local web interface, supporting batch questions, multi-select, and free text for human-in-the-loop interactions.

Metabase includes a built-in Model Context Protocol (MCP) server that lets AI clients connect directly to a Metabase instance. It uses the Streamable HTTP transport and builds on Metabase's Agent API to expose tools for searching, exploring, querying, and visualizing data — all scoped to the connecting user's permissions.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Connects AI agents to anonymous strangers for asking and answering questions in character.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

Enables Claude to answer plain-English questions by listing and describing database tables, running read-only SQL queries, and searching a folder of policy documents.

A high-performance Model Context Protocol server for AI integration with Metabase analytics platforms. Features response optimization, robust error handling, and comprehensive data access tools.

Query and manage Metabase dashboards, cards, and data via Claude

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

Enables loading CSV text, filtering and aggregating datasets over Streamable HTTP, and optionally using Amazon Bedrock to turn query results into concise answers suitable for speech.

An MCP server that gives an AI agent scoped, safe access to your Postgres databases with per-connection access control, row caps, timeouts, and defense-in-depth read-only enforcement.

Enables AI assistants to interact with Metabase by providing access to dashboards, questions, and databases through the Metabase API. It allows users to list resources, execute existing cards, and run custom SQL queries to retrieve data through natural language.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

Automatically routes natural language questions to RAG or Text2SQL paths to answer queries about virtual construction site data, supporting semantic search and structured aggregation.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables AI agents to read-onlyly access Metabase instances, query databases using MBQL or SQL, explore schemas, run saved questions, and export data.

Enables AI assistants to interact with Metabase for querying databases, executing SQL, managing dashboards, and automating analytics workflows.

Enables AI agents to create, submit answers, and query profile questions from the White Rabbit Profile Questions API. Supports various question types and batch operations.

MCP server for answering questions about official statistics from a single publication URL, with tools to check query scope, retrieve overview, text, data files, and search.

A TypeScript/Node.js MCP server that wraps the Metabase REST API, enabling AI agents to execute queries, explore schemas, and build dashboards through structured tool calls.

Enables AI assistants to interact with Metabase analytics platform, allowing them to query databases, execute SQL, manage dashboards and cards, and access analytics data through natural language.

Enables a weaker agent to consult a bare frontier model over any OpenAI-compatible endpoint on demand, enforcing when to ask, how to ask in self-contained form, and how to verify and arbitrate the returned hypothesis. It also supports auditing an artifact against a checklist into a structured defect list with a verdict, plus optional read-only server-side evidence gathering for follow-up rounds.

Enables any MCP-compatible AI agent to ask humans questions in real time via a mobile-friendly PWA with push notifications, operating local-first without third-party services.

Connect AI assistants to your Metabase analytics platform. Access dashboards, execute queries, and retrieve data seamlessly through conversational interfaces. Enhance your analytics experience with structured data access and robust error handling.

Enables AI agents to search and discover data across SQLite and CSV sources through an MCP interface, with metadata indexing and fuzzy search capabilities.

MCP server for Metabase that gives AI agents full access to query, explore, and manage content in your Metabase instance.

MCP server to access India Open Government Data (data.gov.in) resources via natural language queries.

Enables AI assistants to interact with Metabase analytics platform, allowing them to query databases, manage dashboards and cards, execute SQL queries, and access analytics data through natural language.

Enables AI assistants in MCP-compatible clients to list topics, fetch random junior, mid, or senior AI Engineer questions with scoring points, and retrieve a free self-checker link for answer practice.

Enables MCP clients to ask natural-language business questions over a retail dataset, keep multi-turn conversations, receive spoken text with structured cards, generate weekly briefs, and submit corrections for improved answers.

Enables AI assistants to interact with Metabase analytics platform, allowing users to query databases, manage dashboards and cards, execute SQL queries, and access analytics data through natural language.

Enables MCP clients to work with a self-hosted Metabase instance through its REST API using a static bearer token instead of OAuth. Exposes tools for running SQL or MBQL queries, browsing databases and tables, and creating, updating and organizing questions, dashboards, collections and metrics.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Headless MCP server for Metabase: 161 tools for queries, dashboards, admin and more. Plain API-key auth with no OAuth or browser, stdio or HTTP, works on any Metabase version and tier.

Connects AI assistants to Metabase for database queries, SQL execution, dashboard management, and analytics workflows via natural language.

Enables agents to ask users questions through rich, browser-rendered HTML forms and receive structured answers, supporting approvals, choices, free-text, and form inputs.

MCP server adapter that exposes A-share stock data tools, prompts, and resources via FastMCP, enabling querying of stocks, K-lines, financials, sectors, and market hot spots through natural language.

Enables AI assistants to query hundreds of models across OpenAI, Google, and OpenRouter, with model discovery, deep-research jobs, and image generation.

Enables AI agents to read and optionally write to PostgreSQL databases through a multi-project setup with schema inspection, query execution, and performance analysis tools.

Provides read-only tools to search and retrieve timestamped transcript evidence from the Pinkbike Podcast, enabling bike research questions to be answered with cited source passages.