HomeSkills › Lark / Feishu Skill via OpenAPI MCP servers (300+ tools)
Automation & Workflows

Lark / Feishu Skill via OpenAPI MCP servers (300+ tools)

2K downloads 1 stars Version 1.0.0 Rank #6653 of 10,000+

What this skill does

Based on FeiShu(飞书) / Lark's OpenAPI MCP server, manage user information, chats, emails, cloud documents, multidimensional tables, tasks, calendars, etc.

Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) is part of the Automation & Workflows category — automation and workflow skills that schedule, trigger, and orchestrate tasks. You can install it on its own or alongside other automation & workflows skills from the OpenClaw catalog.

Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) is ranked #6653 by downloads in the OpenClaw skill catalog (2K total downloads, 1 stars). It belongs to the Automation & Workflows category alongside 1059 other top-10000 skills.

How to install Lark / Feishu Skill via OpenAPI MCP servers (300+ tools)

The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:

  1. Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
  2. Open the in-app Skills panel.
  3. Search for mcp-lark and click Install.
  4. The skill activates automatically when an incoming message matches its description.

Install from the command line

If you already run the OpenClaw CLI, add Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) with a single command:

openclaw skills add mcp-lark

This pulls mcp-lark from ClawHub and installs it into ~/.openclaw/skills/mcp-lark/. Restart the OpenClaw gateway afterwards so the new skill is discovered.

How to use Lark / Feishu Skill via OpenAPI MCP servers (300+ tools)

Once installed, Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.

Manual install (advanced)

If you prefer manual installation:

  1. Click the Download .zip button above to grab mcp-lark-1.0.0.zip directly from our S3 mirror.
  2. Unzip into ~/.openclaw/skills/mcp-lark/ (create the directory if it does not exist).
  3. Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.

Frequently asked questions

How do I install Lark / Feishu Skill via OpenAPI MCP servers (300+ tools)?

Install Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) in the OpenClaw Easy desktop app by opening the Skills panel, searching for mcp-lark, and clicking Install. From a terminal you can run: openclaw skills add mcp-lark. Either way the skill is placed in ~/.openclaw/skills/mcp-lark/.

Is Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) free?

Yes. Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) is free and open-source, distributed under the Apache-2.0 license through ClawHub. No account or payment is required to download or run it.

What does Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) do?

Based on FeiShu(飞书) / Lark's OpenAPI MCP server, manage user information, chats, emails, cloud documents, multidimensional tables, tasks, calendars, etc.

Related: more automation & workflows skills

If Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) looks useful, you may also want to check out other automation & workflows skills in the OpenClaw catalog:

Browse the full OpenClaw skill catalog

This page covers just one skill. The OpenClaw skill hub has 10,000+ more — search, sort by downloads or stars, and install any of them in one click. There is also a curated awesome-openclaw-skills list grouped by use case.

Get OpenClaw Easy — Free

Install Lark / Feishu Skill via OpenAPI MCP servers (300+ tools) and 10,000+ other OpenClaw skills in one click. Free, open-source, runs locally on macOS & Windows.

Free, open-source · Apache-2.0 · Works with Claude, ChatGPT, Gemini, or local Ollama models