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communication

Lark▌

by lorrylockie

Connect seamlessly to the Lark workplace platform to access employee info and messaging with secure, automatic authentic

Provides a bridge to Lark/Feishu workplace collaboration platform, enabling access to employee information and messaging capabilities with automatic authentication and token management.

github stars

★ 3

GitHubnpm
Automatic token managementMultiple credential configuration options

best for

  • / HR teams managing employee directories
  • / Organizations using Lark/Feishu for workplace collaboration
  • / Automating employee lookup workflows

capabilities

  • / Query employee information by ID
  • / Access Lark Contact API data
  • / Manage authentication tokens automatically
  • / Handle Lark/Feishu API interactions

what it does

Connects to Lark/Feishu workplace platform to query employee information and access messaging features through automated API integration.

about

Lark is a community-built MCP server published by lorrylockie that provides AI assistants with tools and capabilities via the Model Context Protocol. Connect seamlessly to the Lark workplace platform to access employee info and messaging with secure, automatic authentic It is categorized under communication.

how to install

You can install Lark in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Lark is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Lark MCP Server

A Model Context Protocol (MCP) server that integrates with Lark/Feishu APIs, allowing LLMs to interact with Lark services.

Features

  • Query employee information using Lark's Contact API
  • More features coming soon...

Prerequisites

  • Node.js 16 or higher
  • A Lark/Feishu application with App ID and App Secret
  • Claude for Desktop or another MCP client

Installation

npm install
npm run build

Usage

You can run the server in two ways:

1. Using Command Line Arguments (Recommended)

npx lark-mcp <app_id> <app_secret>

Replace <app_id> and <app_secret> with your Lark application credentials.

2. Using Environment Variables

export LARK_APP_ID=your_app_id
export LARK_APP_SECRET=your_app_secret
npx lark-mcp

Available Tools

get-user-info

Retrieves employee information using their ID.

Example usage in Claude:

Please look up employee information for ID 12345

Development

  1. Clone the repository
  2. Install dependencies: 
    npm install
  3. Build the project: 
    npm run build
  4. Start the server in development mode: 
    npm run dev

Configuration

The server prioritizes credentials in the following order:

  1. Command line arguments
  2. Environment variables
  3. Default values (if any)

Error Handling

  • The server will validate credentials before starting
  • API errors are properly handled and returned to the client
  • Detailed error messages help with troubleshooting

License

MIT

Contributing

  1. Fork the repository
  2. Create your feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a new Pull Request

FAQ

What is the Lark MCP server?
Lark is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Lark?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.5★★★★★10 reviews
  • ★★★★★Shikha Mishra· Oct 10, 2024

    Lark is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • ★★★★★Piyush G· Sep 9, 2024

    We evaluated Lark against two servers with overlapping tools; this profile had the clearer scope statement.

  • ★★★★★Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Lark is the kind of server we cite when onboarding engineers to host + tool permissions.

  • ★★★★★Sakshi Patil· Jul 7, 2024

    Lark reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • ★★★★★Ganesh Mohane· Jun 6, 2024

    I recommend Lark for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • ★★★★★Oshnikdeep· May 5, 2024

    Strong directory entry: Lark surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • ★★★★★Dhruvi Jain· Apr 4, 2024

    Lark has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • ★★★★★Rahul Santra· Mar 3, 2024

    According to our notes, Lark benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • ★★★★★Pratham Ware· Feb 2, 2024

    We wired Lark into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★Yash Thakker· Jan 1, 2024

    Lark is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.