"A platform for collaboration and communication - Feishu" matching MCP servers:

Provides enrollment data query, aggregation, and cross-table comparison from Feishu multi-dimensional tables for AstrBot.

Enables reading, creating, updating, and appending Feishu documents, as well as querying and updating Bitable fields and records via the MCP protocol.

Enables interaction with Feishu (Lark) multidimensional tables (Bitable) through MCP tools, supporting operations like creating/updating/querying records, batch operations, and application management with automatic token refresh.

Enables interacting with Feishu (Lark) multidimensional tables through MCP tools. Supports listing tables, reading records, searching records and apps, and getting views.

An internal MCP server providing Database (SQL execution) and Server (Linux SSH/SFTP) skills with 11 tools, enabling remote execution, risk control, and full audit via Claude Code or other clients.

飞书多维表格

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

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.

MCP server for tracking user course progress, providing tools to retrieve and save course and stage progress for authenticated users with data persisted in SQL Server.

MCP server platform enabling agents to self-register and access geo MCP tools (read-only geo_entities) plus hello ping services via a public MCP endpoint.

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

High-performance Model Context Protocol server supporting multiple LLM providers (OpenRouter, OpenAI, Groq) with WebSocket API and conversation history persistence.

Enables governed, read-only SQL analytics, hybrid RAG knowledge search, financial metric calculation, and database schema introspection through MCP, with role-based access control, audit logging, and AI observability.

Enables LLMs to interact with Feishu Base (Lark) databases by providing comprehensive tools for managing records, tables, and schemas. It supports full CRUD operations on database entries and structural modifications to table fields through the Model Context Protocol.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

Bootstrap MCP server for future data exploration and querying across multiple databases, currently only provides a hello_world tool with no actual data connectivity.

Turns any LLM into a coding co-pilot with production-ready MCP server providing lint, test, execution, generation, and graph tools. Features Neo4j persistence, OpenAI Agent integration, REST API, and React frontend for comprehensive code development assistance.

A powerful AI service platform that provides complete MCP tool calling capabilities and RAG knowledge base functionality, enabling users to connect to multiple MCP servers and perform intelligent document search.