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 CrewAI 10 tools — connect in under 2 minutes

Name: Feishu Bitable
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Feishu Bitable through Vinkius, pass the Edge URL in the `mcps` parameter and every Feishu Bitable tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Feishu Bitable Specialist",
    goal="Help users interact with Feishu Bitable effectively",
    backstory=(
        "You are an expert at leveraging Feishu Bitable tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Feishu Bitable "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

When paired with CrewAI, Feishu Bitable becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Feishu Bitable tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Feishu Bitable

Why Use CrewAI with the Feishu Bitable MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Feishu Bitable through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Feishu Bitable + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Feishu Bitable for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Feishu Bitable, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Feishu Bitable tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Feishu Bitable against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Feishu Bitable MCP Tools for CrewAI (10)

These 10 tools become available when you connect Feishu Bitable to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Feishu Bitable + CrewAI FAQ

Common questions about integrating Feishu Bitable MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.