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

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.

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.

An MCP App that enables AI agents to ask users multiple questions with tab-based navigation, multiple-choice options, multi-select support, and custom text input, all rendered inline in the conversation.

Enables AI assistants to answer questions about the operator's current focus, engagements, reusable patterns, availability, and service offerings, with responses grounded in structured data and including confidence labels and source citations.

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

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.

Connects Metabase business intelligence platform to AI assistants, enabling users to query data, create dashboards and charts, manage databases, and interact with BI assets using natural language through the Model Context Protocol.

Enables AI-powered interaction with Metabase instances and PostgreSQL databases through natural language. Creates models, SQL queries, metrics, and dashboards using both Metabase API and direct database connections.

Persistent memory and pattern learning for AI coding assistants via MCP.

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.

Enables users to search Samin Yasar's video library and receive full-video recommendations grounded in transcript evidence with links to exact matched caption cues.

Lightweight TypeScript MCP server for Airtable base discovery, table/view queries, record CRUD, and validated filterByFormula construction.

A general-purpose MCP server that lets AI work with multiple databases within clear boundaries.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Semantic navigator for MCP tools that finds relevant tools by natural language intent, reducing token usage by 95%.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.

A read-only natural-language database agent that exposes PostgreSQL schema-discovery and SELECT tools via MCP, enabling users to query databases in plain English.

Enables interaction with Plaid's financial data API to sync bank transactions and retrieve account balances with secure encrypted token storage.

Searches Reddit for answers to questions and saves Q&A sessions to Notion.