lark-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| lark_send_messageB | 发送消息到飞书聊天 |
| lark_reply_messageC | 回复飞书消息 |
| lark_list_chatsB | 列出飞书群聊列表 |
| lark_get_chat_membersC | 获取群聊成员列表 |
| lark_list_messagesC | 查看聊天历史消息 |
| lark_send_cardB | 发送交互卡片到飞书聊天 |
| lark_get_user_infoA | 获取飞书用户信息，不传 user_id 查自己 |
| lark_get_agendaC | 查看飞书日程安排 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Each tool targets a distinct resource and action: sending, replying, listing chats, getting members, viewing messages, sending cards, user info, and agenda. While send_message and send_card both send to a chat, their descriptions clearly distinguish text from interactive cards, leaving no ambiguity.
All tool names follow the same pattern: lark_verb_noun (e.g., lark_send_message, lark_list_chats). The verbs are consistent (send, reply, list, get) and all use snake_case, making the naming uniform and predictable.
With 8 tools, the server is well-scoped for a collaboration platform covering messaging, chat management, user info, and agenda reading. Each tool earns its place without being overwhelming or sparse.
The server covers core messaging workflows (send, reply, list history) and read operations for chats and users, but lacks write operations for chats (create/update/delete), message editing/deletion, and calendar management beyond reading. These gaps could cause agents to hit dead ends when trying to manage resources.