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How to Use the CompanyCam MCP in Google ADK

Run long-context Gemini reasoning over CompanyCam project files and photos using the Google ADK.

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Google ADK

Connect CompanyCam MCP to Google ADK

Create your Vinkius account to connect CompanyCam 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 Photo Collections in Google ADK

This MCP Server exposes `list_all_photos` and `list_project_photos` to feed your Gemini models with real-time jobsite imagery. The Google ADK passes these image references directly into Gemini's massive context window for multi-photo analysis. Instead of processing images one by one, your agent can cross-reference hundreds of construction photos at once. It uses the tool outputs to detect progress trends or identify safety violations across entire projects.

Map Construction Data to Google Cloud

The `list_projects` and `search_projects` tools allow your agent to pull structured construction data directly into your Google ADK pipeline. This MCP Server integration lets you join live field updates with historical enterprise data stored in BigQuery. Your agent can run complex reasoning loops on Vertex AI, matching active project details with supply chain databases. The tool output feeds clean project names and IDs directly into your cloud-hosted analytics models.

Coordinate Field Documents and Teams

The `list_project_documents` tool gives your Google ADK agent direct access to PDF contracts and site permits. It pairs this with `list_users` to see which field superintendent is assigned to the active jobsite. Because the ADK handles tool execution natively, your agent can automatically pull a document, read its contents, and match it against the user details retrieved by `get_current_user` to verify signing status.

Setup guide

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

Use the `McpToolset` class with your Vinkius HTTP URL. Pass this toolset instance into your `LlmAgent` configuration to expose the construction tools directly to Gemini.
Yes, the `McpToolset` supports an optional `tool_names` filter. This allows you to expose only read tools like `get_project` while hiding write operations like `create_project`.
Gemini's million-token context window easily digests the large JSON arrays returned by `list_all_photos` or `list_project_documents`. This makes it perfect for analyzing entire project histories without running out of memory.
Yes, the toolset supports both Stdio and HTTP transports. You can run your agent locally or host it on Cloud Run while keeping the connection to the API secure.
Vinkius operates under a zero-trust model, routing your project names, photo URLs, and document lists through ephemeral V8 isolates that never write your construction data to persistent storage.

Start using the CompanyCam MCP today

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