Feishu Business Operations
LocalAbout Feishu Business Operations
Feishu Business Operations is an MCP server for teams managing Feishu/Lark Bitable tables and approvals. Its scenario-based tools cover table operations, AI-assisted schema design, and approval tracking and analysis.
Key features
- 01Search and query Bitable tables
- 02Batch upsert records
- 03Create tables and define fields
- 04Design schemas from descriptions with AI
- 05List, alert on, and analyze approvals
Use cases
- 01Find tables and inspect matching records
- 02Write batches of business records
- 03Draft a table schema from a business need
- 04Identify delayed approvals and review statistics
MCP support
The server exposes eight Feishu/Lark Bitable and approval tools to MCP clients, including search, queries, writes, creation, schema design, alerts, and statistics.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y feishu-scenarios-mcpFEISHU_APP_IDFEISHU_APP_SECRETSecretFEISHU_BITABLE_APP_TOKENSecretFEISHU_ENVFEISHU_USER_IDDEEPSEEK_API_KEYSecretLocal servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
8Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| keyword | string | No | Table name keyword; supports fuzzy search. Leave blank to return the first 10 tables. |
Details
From the project READMEfeishu-scenarios-mcp
AI-native business operations MCP server for Feishu/Lark. 8 scenario-based tools covering multidimensional tables (Bitable) and approvals — search, query, write, create, AI schema design, approval tracking, alerts, and statistics.
Installation
npm install -g feishu-scenarios-mcp
Or run directly:
npx feishu-scenarios-mcp
Configuration
Create a .env file with your Feishu app credentials:
FEISHU_APP_ID=cli_xxxxxxxxxxxx
FEISHU_APP_SECRET=xxxxxxxxxxxxxxxxxxxxxxxx
FEISHU_BITABLE_APP_TOKEN=xxxxxxxxxxxx
FEISHU_ENV=feishu
| Variable | Required | Description |
|---|---|---|
FEISHU_APP_ID | Yes | Feishu app ID from Developer Console |
FEISHU_APP_SECRET | Yes | Feishu app secret |
FEISHU_BITABLE_APP_TOKEN | For bitable | Bitable app token |
FEISHU_ENV | No | feishu (default) or lark |
FEISHU_USER_ID | For approval | Your Feishu user open_id |
DEEPSEEK_API_KEY | For schema AI | DeepSeek API key for AI table design |
Claude Desktop Setup
Add to your claude_desktop_config.json:
{
"mcpServers": {
"feishu-scenarios": {
"command": "npx",
"args": ["-y", "feishu-scenarios-mcp"],
"env": {
"FEISHU_APP_ID": "cli_xxxxxxxxxxxx",
"FEISHU_APP_SECRET": "xxxxxxxxxxxxxxxx",
"FEISHU_BITABLE_APP_TOKEN": "xxxxxxxxxxxx",
"FEISHU_ENV": "feishu"
}
}
}
}
Tools
Bitable (多维表格)
| Tool | Description |
|---|---|
bitable_search | Search tables by keyword. Returns table ID, name, field preview, record count. |
bitable_query | Query records with optional filters. |
bitable_upsert | Batch write records. Auto field-name matching and type conversion. |
bitable_create | Create a new table with field definitions. |
bitable_schema_ai | AI-designed table schema from business description. Requires DEEPSEEK_API_KEY. |
Approval (审批)
| Tool | Description |
|---|---|
approval_list | Query approval instances by status, type, applicant, time range. |
approval_alerts | Find bottlenecks and overtime approvals. Default threshold 48h. |
approval_stats | Approval statistics: by status, type, month, top applicants. |
Usage Examples
Search tables:
"搜一下包含'审批'的表格"
Query records:
"查一下积压跟踪表里 pending 状态的记录"
Write records:
"往跟踪表写一条记录,负责人张三,状态待处理"
AI design table:
"帮我设计一张跟踪审批积压的表"
Approval alerts:
"谁审批最慢"
Approval statistics:
"本月审批通过率"
Feishu Bot (Mobile)
The package also includes a WebSocket-based Feishu bot for mobile access:
npx feishu-scenarios-mcp-bot
Setup guide: docs/bot-setup.md
Required Feishu Permissions
approval:instance— read approval instancesbitable:app— access bitableim:message— bot messagingim:message:send_as_bot— send bot messages
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.