How do I find my Feishu/Lark App ID and Secret?

Log in to the [Feishu Open Platform](https://open.feishu.cn/), create a new application or select an existing one, and you will find your App ID and App Secret in the 'Credentials' section.

Where can I find the 'appToken' for my Bitable base?

The `appToken` is the unique identifier found in the URL of your Bitable base. It typically looks like `AppbcbWCzen6D8dezhoCH2RpMAh` and appears after `/base/` in the browser address bar.

Does my application need specific permissions?

Yes. Ensure your application has the 'View, comment, edit and manage Bitable' (bitable:app) permission enabled in the Developer Console and that the bot is added as a collaborator to the base.

Feishu Bitable MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Feishu Bitable
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Feishu Bitable through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Feishu Bitable "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Feishu Bitable?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

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High SecurityEnterprise-grade

IAMAccess control

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DLPData protection

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Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Feishu Bitable MCP Server

Empower your AI agent to orchestrate your data with Feishu Bitable (Lark), the leading multi-dimensional table platform for modern collaboration. By connecting Feishu Bitable to your agent, you transform complex database management and record tracking into a natural conversation. Your agent can instantly list your tables, retrieve field schemas, manage records (create, update, delete), and even search through your data without you needing to navigate the web interface. Whether you are managing a project tracker, a customized CRM, or an asset database, your agent acts as a real-time data assistant, keeping your bases organized and your team aligned.

Pydantic AI validates every Feishu Bitable tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Base Orchestration — Retrieve metadata about your Bitable bases and list all tables within them.
Data Operations — Manage table records with full support for batch creation, listing, and granular updates.
View & Field Auditing — Browse defined views and field schemas to understand your data structures.
Advanced Search — Search through records using filter expressions to find exactly what you need.
Team Alignment — Access base information to ensure your AI agent has the correct context for your collaboration.

The Feishu Bitable MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Feishu Bitable to Pydantic AI via MCP

Follow these steps to integrate the Feishu Bitable MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Feishu Bitable with type-safe schemas

Why Use Pydantic AI with the Feishu Bitable MCP Server

Pydantic AI provides unique advantages when paired with Feishu Bitable through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Feishu Bitable integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Feishu Bitable connection logic from agent behavior for testable, maintainable code

Feishu Bitable + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Feishu Bitable MCP Server delivers measurable value.

Type-safe data pipelines: query Feishu Bitable with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Feishu Bitable tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Feishu Bitable and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Feishu Bitable responses and write comprehensive agent tests

Feishu Bitable MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Feishu Bitable to Pydantic AI via MCP:

create_records

Batch create records in a table

delete_record

Delete a record from a table

get_base_info

Get Bitable base information

get_record_details

Get record detailed data

list_fields

List fields in a table

list_records

List records in a table

list_tables

List tables in a Bitable app

list_views

) defined for a table. List views in a table

search_records

Search records with filter

update_record

Update an existing record

Example Prompts for Feishu Bitable in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Feishu Bitable immediately.

"List all tables in Bitable base 'AppbcbWCzen6D8dezhoCH2RpMAh'."

"Add a new record to the 'Inventory' table with fields: Name='MacBook Pro', Quantity=5."

"Search for records in table 'tblsRc9GRRXKqhvW' where 'Status' equals 'Shipped'."

Troubleshooting Feishu Bitable MCP Server with Pydantic AI

Common issues when connecting Feishu Bitable to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Feishu Bitable + Pydantic AI FAQ

Common questions about integrating Feishu Bitable MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Feishu Bitable MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.