How to Use the JobNimbus MCP in Google ADK

Q: How do I initialize the JobNimbus toolset within the Google ADK?

Bottom line: you install the library and use McpToolset with the HTTP transport pointing to your Vinkius endpoint. Pass this toolset directly into your LlmAgent constructor inside your Python script. Your Google ADK agent can then immediately call JobNimbus tools like listjobs and listtasks during its reasoning loops.

Q: Can I restrict which JobNimbus tools my Google ADK agent can see?

Yes, you can use the optional toolnames filter when defining your McpToolset in Python. This allows you to expose only read-only tools like listcontacts and listproducts to public-facing Google ADK agents. It guarantees that sensitive JobNimbus tools like listpayments remain completely hidden from unauthorized models.

Connect Gemini models to your JobNimbus construction pipeline with the Google ADK to run deep CRM analysis on Vertex AI.

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Connect JobNimbus MCP to Google ADK

Create your Vinkius account to connect JobNimbus 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 JobNimbus with Google ADK

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Enterprise Job Analysis using Google ADK and Gemini

Feed your entire JobNimbus history into Gemini's massive context window using the Google ADK to analyze construction project bottlenecks. By pulling active projects with `list_jobs` and detailed workflows with `list_workflows`, your Google ADK agent can process hundreds of active JobNimbus files simultaneously. This allows the Gemini model to spot operational delays across your entire JobNimbus pipeline that standard dashboards miss. This MCP Server exposes raw JobNimbus data directly to your Google ADK `LlmAgent` for deep analysis. You can combine this real-time JobNimbus pipeline data with historical construction metrics in BigQuery using your Google ADK agent. Your Google ADK agent can then compare past project performance against current JobNimbus statuses to predict roofing completion dates.

Automated Field Resource Coordination on Google Cloud

Coordinate your field teams by letting your Google ADK agent manage scheduling and task assignments across your JobNimbus account. The Google ADK agent uses `list_tasks` to check active construction duties and matches them against your JobNimbus roster using `list_users`. Because the Google ADK connects directly to our MCP Server, you can trigger these JobNimbus updates based on Google Cloud Pub/Sub events. When a construction milestone falls behind, your Google ADK agent can look up the associated JobNimbus project details using `get_job`. The Gemini model then drafts internal Google Chat updates or reassigns the JobNimbus task to an available technician. This keeps your JobNimbus tasks moving without requiring your Google ADK agents or project managers to manually review boards every morning.

BigQuery Data Enrichment for JobNimbus Contacts

Enrich your customer records by cross-referencing your JobNimbus CRM with enterprise data warehouses using the Google ADK. Your Gemini agent can search for JobNimbus customers using `list_contacts` and pull deep profile details with `get_contact`. The Google ADK then matches these JobNimbus records against your marketing databases in BigQuery to build detailed profiles. This integration gives your Google ADK agent immediate access to JobNimbus histories alongside Google Cloud data like regional weather patterns. When auditing available services using `list_products`, your Google ADK agent can recommend specific JobNimbus packages tailored to that customer's exact location.

Setup guide

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

Bottom line: you install the library and use `McpToolset` with the HTTP transport pointing to your Vinkius endpoint. Pass this toolset directly into your `LlmAgent` constructor inside your Python script. Your Google ADK agent can then immediately call JobNimbus tools like `list_jobs` and `list_tasks` during its reasoning loops.

Yes, you can use the optional `tool_names` filter when defining your `McpToolset` in Python. This allows you to expose only read-only tools like `list_contacts` and `list_products` to public-facing Google ADK agents. It guarantees that sensitive JobNimbus tools like `list_payments` remain completely hidden from unauthorized models.

The Google ADK allows Gemini to ingest massive lists of JobNimbus contacts and jobs in a single turn. When you call `list_jobs` or `list_contacts`, the Google ADK agent can hold thousands of CRM records in its active memory. This lets the Gemini model perform complex, multi-step reasoning across your entire JobNimbus pipeline without losing context.

Yes, Vinkius manages the server hosting, but you connect to it securely from your Google Cloud VPC environment using standard HTTP transport. Your Google ADK python application communicates with the MCP Server endpoint using a single secure token. This setup keeps your GCP runtime architecture clean and avoids complex network configurations.

All JobNimbus data, including contact names, project addresses, and workflow statuses, is processed through our secure MCP Server architecture on Vinkius. Vinkius enforces a zero-trust model where data is never cached on disk or used to train Gemini models. Your Google ADK API keys are encrypted at rest and injected into the ephemeral container only at the moment of execution.

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