How to Use the Feishu Bitable MCP in Google ADK

Q: Can I use Google ADK to query Feishu Bitable tables?

Yes, you use the listrecords tool to pull rows directly into your Gemini agent's context window. This allows the model to reason over your live spreadsheet data.

Q: How do I install the Feishu Bitable MCP Server in Google ADK?

Install the package and initialize McpToolset with your Vinkius HTTP URL. Pass that toolset to your LlmAgent instance to make all ten tools instantly available.

Q: Can Google ADK filter specific rows in Feishu Bitable?

The agent uses the searchrecords tool to find rows matching specific criteria. This keeps your token usage low by only importing the exact data your agent needs.

Q: How do I check what columns are available in a table?

Your agent can call listfields to inspect the table schema. It returns the field names and types so the model knows how to format its inputs.

Feed Feishu Bitable base data directly into your Gemini long-context reasoning loops using the Google ADK.

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Connect Feishu Bitable MCP to Google ADK

Create your Vinkius account to connect Feishu Bitable to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Feishu Bitable with Google ADK

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Map enterprise base structures inside Google ADK

The `get_base_info` tool retrieves core metadata about your Bitable application, including its name and ID. Gemini uses this context to ground its reasoning before executing deeper table queries. Combining this with `list_tables` allows the agent to navigate complex relational databases on its own. It dynamically discovers where to pull or push data without developer intervention.

Execute precise updates with this MCP Server

The `update_record` tool modifies specific field values in a targeted Bitable row. Your Gemini agent calls this tool after processing large context windows, writing refined summaries directly back to your table. You can restrict which tools are exposed using the ADK toolset filter. This MCP configuration prevents the agent from accidentally calling destructive operations like `delete_record` in production.

Bulk ingestion from BigQuery to Bitable

The `create_records` tool writes batches of new data into your tables in one go. This is ideal for pipelines that pull structured analytical data from Google Cloud and sync it to collaborative sheets. Because Gemini handles massive token limits, it can format hundreds of rows at once. The ADK toolset then pushes these clean objects straight to the Bitable API.

Setup guide

Set up Feishu Bitable MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Feishu Bitable tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Feishu Bitable_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Feishu Bitable tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Feishu Bitable. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Feishu Bitable MCP in Google ADK

Yes, you use the `list_records` tool to pull rows directly into your Gemini agent's context window. This allows the model to reason over your live spreadsheet data.

Install the package and initialize `McpToolset` with your Vinkius HTTP URL. Pass that toolset to your `LlmAgent` instance to make all ten tools instantly available.

The agent uses the `search_records` tool to find rows matching specific criteria. This keeps your token usage low by only importing the exact data your agent needs.

Your agent can call `list_fields` to inspect the table schema. It returns the field names and types so the model knows how to format its inputs.

Your table schemas and record payloads are processed in transient memory within an isolated execution environment. Vinkius never logs or caches the actual contents of your bases.

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