"React Query" matching MCP servers:

Enables an AI assistant to query and browse multiple database engines read-only, with the ability to switch connections and engines dynamically during a session.

Scrape any webpage and return clean markdown, HTML, or structured JSON. Bypasses anti-bot protection, renders JavaScript (React/Vue/Angular), supports premium residential proxies and CSS extraction. Works with any MCP client — no local install required.

Securely query Dune Analytics with LLMs. Features budget protection, query reuse, and optimized data summaries

Enables LLMs to query live data from over 250+ sources via CData Python Connectors using natural language. Wraps connectors as a Model Context Protocol server.

Open-source agentic schema layer. Define metrics once in YAML, query governed data from any warehouse (Snowflake, BigQuery, Databricks, PostgreSQL, DuckDB) via MCP.

Enables AI tools to query sports tournaments, leaderboards, predictions, and match stats from the Tulidu Sport platform.

Enables Claude to query and manipulate GRID spreadsheets via the GRID API using natural language.

Lets AI agents read and query Wildberries, Ozon, and Yandex Market seller accounts through unified typed tools, with multi-account support, rate limiting, and encrypted credentials.

MCP server for Valorant esports analytics that exposes structured metrics and database query tools, enabling AI-assisted match analysis, player profiling, scouting reports, and coaching insights.

Enables AI agents to query live schema, lineage, and query-context across data warehouses, dbt projects, orchestration systems, and BI tools via MCP tools.

Enables authorized DatumLabMHQ GitHub members to access the Datum data platform through MCP tools such as whoami, list_products, list_questions, ask, query, and health, without holding API keys.

Enables Claude to query a Postgres analytics schema via a read-only MCP server, with tools auto-generated from live database introspection and configurable SQL queries defined in YAML.

Universal Database MCP Server enabling AI assistants to connect and query multiple databases including Databricks, BigQuery, PostgreSQL, MySQL, SQL Server, SQLite, and MariaDB through a unified interface.

Enables LLMs to query and analyze data across multiple MySQL databases with enterprise data federation, intelligent caching, cross-system analytics, and automated schema discovery for comprehensive business intelligence.

Enables users to import, query, edit, audit, and export local personal records through schema-driven MCP tools while masking sensitive fields by default.

A server implementation of MCP for Apache Spark that provides query plans and catalog information to AI systems for query optimization and data discovery.

Enables AI agents to query permission-filtered world views, inspect evidence-backed signals, and trace timelines across integrated enterprise systems, handing deep investigation off to vertical MCP servers via verified capabilities.

Enables AI assistants to query and optionally modify AJEMS workspaces, including apps, forms, and records, without requiring user login.

A single MCP server that lets agents query data through the Greybeam routing layer with Snowflake-compatible tooling.

Enables AI assistants to query and analyze data from Cube.js analytics platforms, allowing natural language access to cubes, measures, dimensions, and complex analytics queries.