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How to Use the BIM 360 Field MCP in Google ADK

Connect BIM 360 Field to your Google ADK pipelines to analyze job site data with Gemini's million-token context.

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Google ADK

Connect BIM 360 Field MCP to Google ADK

Create your Vinkius account to connect BIM 360 Field 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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Feed Construction Logs to Gemini Long Context

Run `list_issues` and `list_tasks` across massive projects and dump the raw output directly into Gemini's massive context window. The Google ADK allows your agent to digest thousands of field logs in a single turn. This MCP Server provides the raw data feed, allowing your enterprise agent to find patterns in safety violations or equipment delays that human inspectors would take weeks to spot.

Sync BIM 360 Field Data with BigQuery

Your Google ADK agents can query `list_companies` and `list_locations` to map subcontractor performance against physical zones. Since the ADK integrates natively with Google Cloud, you can join this live field data with historical tables in BigQuery. This setup turns your agent into an autonomous data pipeline. It extracts current project states and updates your centralized databases without requiring manual export scripts.

Run Enterprise Google ADK Agents on Site Data

Spin up dedicated agents on Vertex AI that monitor project health using `get_project` and `list_issue_types`. The framework handles the translation between Gemini's tool calls and the construction API. You configure the connection using the McpToolset class in your Python code. This MCP server integration exposes the target tools directly to your LLM agent, allowing it to inspect work orders on demand.

Setup guide

Set up BIM 360 Field 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 BIM 360 Field 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="BIM 360 Field_agent",
    model="gemini-2.0-flash",
    instruction="You have access to BIM 360 Field 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 BIM 360 Field. 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 BIM 360 Field MCP in Google ADK

You initialize the connection using the toolset class with the secure HTTP URL provided by Vinkius. Pass this toolset directly into your agent constructor to give Gemini immediate access to your construction data.
Yes, you can pass multiple toolsets to your agent. This allows Gemini to pull active checklists using `list_checklists` and instantly write those records to a BigQuery table in the same execution loop.
Because Gemini models support massive context windows, they easily ingest long lists of issues or tasks. The agent reads the raw JSON output from `list_issues` without running out of memory or losing track of the details.
Yes, you can use the optional tool name filter when instantiating your toolset. This guarantees the agent only discovers lookup tools like `list_projects` and cannot access administrative tools.
All construction checklists, tasks, and issues pass through a zero-trust architecture. The Vinkius runtime executes the MCP Server in an isolated V8 sandbox, ensuring your proprietary field logs are never used for model training or stored on external disks.

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