# Lark Base MCP Server

> Use this tool when you need to integrate large language models (LLMs) with Feishu Base databases, enabling natural language-based data manipulation and schema inspection. It solves problems of data accessibility and automation by providing read and write access to database records through a Model Context Protocol server. This tool is ideal for use cases requiring LLMs to interact with structured data in Feishu Base, with inputs including natural language queries and outputs including manipulated database records.

Canonical page: https://skillsregistry.net/skills/lark-base-team-lark-base-mcp-node-server  
JSON: https://api.skillsregistry.net/v1/skills/lark-base-team-lark-base-mcp-node-server

## Description

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.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/irypmq8bvb)
- **Repository:** <https://github.com/Lark-Base-Team/lark-base-mcp-node-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "lark-base-team-lark-base-mcp-node-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lark-base-team-lark-base-mcp-node-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lark-base-team-lark-base-mcp-node-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt