"How to Use or Manage Knowledge Base in Feishu" matching MCP servers:

Enables semantic search and document management with support for text, PDF, and image uploads using your own Supabase database and OpenAI API keys. Supports multi-tenant deployment on Cloudflare Workers or local hosting.

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.

A Model Context Protocol server that provides LLMs with read and write access to Feishu Base (飞书多维表格) databases, enabling them to inspect schemas and manipulate records through natural language.

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 Claude to save, retrieve, update, search, and organize personal ideas and reusable analytical frameworks in a private SQLite-backed knowledge base. Supports local desktop use or always-on access across a user's own devices over a private network.

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.

MCP server for executing Databricks SQL queries and comparing table data, supporting CLI and VS Code integration.

Enables LLMs to manage file-based knowledge bases with dual storage (Markdown + SQLite). Supports creating, searching, and organizing articles across multiple knowledge bases with full-text search capabilities.

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

飞书多维表格

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Provides a production-ready Model Context Protocol server with dual STDIO and Streamable HTTP transports, enabling file operations, memory, database queries, RAG, web search, GitHub integration, background tasks, and prompt-based workflows.

Turns any OData V2 or V4 service, SAP Gateway included, into MCP tools that AI clients such as Claude, ChatGPT, Copilot, and Cursor can call without code by reading $metadata. It lets models discover entity sets and fields, then query services through built-in read-only tools.

An embedded knowledge graph in one SQLite file, exposing a MCP server for agents to read and write entities and relationships with full audit trail and time travel.

A persistent memory server that implements a local knowledge graph using the Kuzu embedded database to store entities, relationships, and observations. It enables AI models to maintain structured long-term context through searchable nodes and comprehensive tag-based organization.

Builds and manages a cardiology-focused knowledge graph in Neo4j by extracting medical entities and relationships from documents using LLMs. It enables users to ingest PDFs, refine extracted data, and perform natural language queries to gain clinical insights.

An MCP server that lets LLM agents accumulate organizational knowledge across sessions, scoped by domain, backed by Neo4j with enforced structural invariants.

A TypeScript MCP server for managing persistent knowledge graphs with entities, directional relations, and time-based observations. It enables users to create, search, and track structured information with built-in concurrency control and JSON file storage.