About feishu-tools-mcp
feishu-tools-mcp is an MCP server that gives AI coding agents such as Cursor access to Feishu operations. The README lists document reading, messaging, contract approval and data processing, though only document reading is documented as a tool. It suits teams working across Feishu and AI tools.
Key features
- 01Reads Feishu document content as plain text
- 02Authenticates with a self-built app token
- 03Configured via App ID and App Secret in .env
- 04Runs as an MCP server in Cursor
Use cases
- 01Having an AI read and summarize Feishu documents
- 02Passing Feishu document links to Cursor agent mode
- 03Combining Feishu data with AI-driven processing
MCP support
This project is an MCP server that exposes a get_feishu_doc tool to MCP clients such as Cursor, returning Feishu document content as plain text.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMElark-tools-mcp
MCP server provides Feishu related operations to AI encoding agents such as cursor
飞书MCP插件
通过打通飞书与cursor,向LLM提供读取文档、发送消息、合同审批、数据处理.....
可能会有意想不到的组合方式
创建自建应用
MCP服务运行基于token,需要创建一个应用并做发布 https://open.feishu.cn/document/server-docs/api-call-guide/terminolog
然后对应用进行文档授权,这一步较为繁琐,参考文档,选择合适的方案:https://open.feishu.cn/document/uAjLw4CM/ugTN1YjL4UTN24CO1UjN/trouble-shooting/how-to-add-permissions-to-app
运行服务
- 拷贝 .env.example 为 .env 文件
- 修改 .env 文件中的 FEISHU_APP_ID 为飞书自建应用的 app_id
- 修改 .env 文件中的 FEISHU_APP_SECRET 为飞书自建应用的 app_secret
- 运行 MCP Server
yarn installyarn start - Add MCP to cursor
- Agent 模式下,输入飞书文档链接,让AI帮你阅读与整理内容
效果

tools
get_feishu_doc
获取飞书文档信息(纯文本)
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.