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Lark rs MCP Server

@hanxuanliang

Repository

Basic information

Category

Communication

License

MIT

Transports

stdio

Author

hanxuanliang

About Lark rs MCP Server

lark rust mcp server

#larkrs#mcp#feishu-api

Lark rs MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "larkrs-mcp": {
      "command": "/Users/code/mcp/larkrs-mcp/target/debug/larkrs-mcp",
      "env": {
        "FEISHU_APP_ID": "<your-app-id>",
        "FEISHU_APP_SECRET": "<your-app-secret>"
      }
    }
  }
}

Lark rs MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Lark rs MCP?

Lark rs MCP is a server that implements the Model Context Protocol (MCP) to integrate with Feishu (Lark) APIs. It enables AI models to interact with Feishu services, specifically reading metadata and content from multidimensional tables and batch-creating records. It is designed for developers and AI applications that need to access Feishu data through the MCP standard.

How to use Lark rs MCP?

Clone the repository, then compile with cargo build. Point the MCP client's command to the compiled binary path. At runtime, set environment variables following the .env.example format for Feishu authentication. Currently only STDIO mode is supported, and the server has been tested with the Chatwise client.

Key features of Lark rs MCP

  • Reads metadata and content from Feishu multidimensional tables
  • Supports batch creation of records in multidimensional tables
  • Communicates via STDIO (standard input/output) only
  • Written in Rust for performance and reliability

Use cases of Lark rs MCP

  • Connect AI assistants to Feishu table data for real‑time queries
  • Automate bulk record creation in Feishu from AI‑driven workflows
  • Enable chatbots to retrieve and display structured Feishu content

Frequently asked questions

1

What Feishu features does Lark rs MCP support?

Currently it supports reading metadata and content from multidimensional tables and creating records in batch.

2

What transport mode does Lark rs MCP use?

Only STDIO mode is supported, suitable for CLI and embedded application scenarios.

3

How do I configure and run Lark rs MCP?

Clone the repository, compile with `cargo build`, set the binary path in your MCP client, and provide environment variables for Feishu authentication as shown in `.env.example`.

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