How to Use the Weiban Assistant MCP in Google ADK

Q: What if I need historical chat records with Weiban Assistant and Google ADK?

You run listchatrecords. Since the Google ADK supports long context, your agent can hold weeks or months of conversation history while analyzing it against other enterprise data.

Q: Can Weiban Assistant and Google ADK help track sales leads?

The server provides listleads to show all current prospects. The agent uses this list, alongside staff stats from getstaffstats, to build a complete picture of the sales pipeline.

Q: Does Weiban Assistant and Google ADK help with organization structure?

Yes. You can get an activity summary via getorgsummary or list all personnel using liststaff. This helps map operational roles to observed behavior.

Weiban Assistant for Google ADK: Analyze deep messaging data and customer records with BigQuery integration.

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Connect Weiban Assistant MCP to Google ADK

Create your Vinkius account to connect Weiban Assistant 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 Weiban Assistant with Google ADK

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Analyzing Customer Relationships via MCP Server

`get_customer_details` lets your agent pull a full profile on any client directly into its reasoning process. Since the Google ADK supports long-context models, it can hold all that data alongside current requests. You're not limited by short memory banks. Want to see who you’ve talked to? Use `list_customers` to get a comprehensive list of everyone in your book.

Tracking Team Activity using Google ADK

`get_org_summary` pulls an organization's activity summary. This data feeds directly into Gemini models, allowing for deep pattern recognition against your BigQuery datasets. You can see high-level trends without manual aggregation. Additionally, the `list_staff` tool provides a roster of employees, which you can cross-reference with other internal Google Cloud data sources.

Managing Group Conversations with MCP Server

`get_group_chat` retrieves details for specific group conversations. The agent reads this context and applies deep reasoning to it—it's built for analyzing large bodies of text, like 1M+ tokens. To see what’s been said lately, run `list_group_chats`. This helps your agents understand the full scope of collaborative discussions.

Setup guide

Set up Weiban Assistant 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 Weiban Assistant 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="Weiban Assistant_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Weiban Assistant 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 Weiban Assistant. 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 Weiban Assistant MCP in Google ADK

Your agent connects to the MCP Server and executes tools like `create_lead`. The results are fed into Gemini models, which can then reason over massive amounts of data held in BigQuery for complex analysis.

You run `list_chat_records`. Since the Google ADK supports long context, your agent can hold weeks or months of conversation history while analyzing it against other enterprise data.

The server provides `list_leads` to show all current prospects. The agent uses this list, alongside staff stats from `get_staff_stats`, to build a complete picture of the sales pipeline.

Yes. You can get an activity summary via `get_org_summary` or list all personnel using `list_staff`. This helps map operational roles to observed behavior.

This server deals with communication and contact information, specifically drawing from tools like `get_customer_details` and `list_customers`.

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