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How to Use the Forj MCP in Google ADK

Feed your Forj community data into Gemini using the Forj MCP Server and Google ADK.

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Google ADK

Connect Forj MCP to Google ADK

Create your Vinkius account to connect Forj 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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Analyze massive activity logs with Google ADK

Gemini's massive context window changes how you handle Forj community moderation. Hook the Forj MCP Server into Google ADK, and your agent can dump thousands of records from `get_user_activity` directly into the prompt. The model can read months of interaction history in a single pass. When a moderator needs context, the agent correlates `search_users` results with external BigQuery data to give a complete picture of the member's standing.

Automate group workflows on Vertex AI

Managing active Forj communities requires constant group adjustments. Your Gemini agent can pull `list_groups` to map out your current structure, then automatically execute `create_group` when it detects missing categories. It doesn't stop at creation. The agent can monitor `list_pending_requests` and selectively fire `add_user_to_group` based on criteria stored in your Google Cloud infrastructure. You get enterprise-grade automation without writing custom API wrappers.

Sync community state with cloud infrastructure

Your Forj setup doesn't exist in a vacuum. By exposing `list_webhooks` to Google ADK, your agent can verify that community events are successfully routing to your Google Cloud functions. It can also run routine audits using `get_account_details` and `list_invitations`. If an invite has been sitting unaccepted for weeks, the agent flags it, keeping your community directory synchronized with your internal CRM.

Setup guide

Set up Forj 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. 1

    Install Google ADK

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

  2. 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. 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. 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 Forj 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="Forj_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Forj tools via MCP.",
    tools=mcp_tools,
)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Forj. 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 Forj MCP in Google ADK

Install google-adk and configure McpToolset with StreamableHttpServerParameters. Pass that toolset directly to your LlmAgent initialization.
Yes. Use the tool_names filter in your McpToolset setup if you only want the agent to access find_user and block it from running create_group.
Gemini's 1M+ token context easily absorbs massive payloads. If you run list_group_members on a massive community, the agent processes the entire list without truncating.
It supports both. For cloud deployments on Vertex AI, you'll likely use the HTTP transport to connect your agent to the managed Vinkius endpoint.
Tools like search_users return raw PII. Vinkius isolates this execution in a zero-trust sandbox, guaranteeing your member data is never logged or stored outside your immediate Google Cloud environment.

Start using the Forj MCP today

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