How to Use the GlassFrog MCP in Google ADK

Q: How do I restrict which GlassFrog tools are exposed to my Google ADK agent?

Use the optional toolnames filter when initializing your Google ADK McpToolset. For example, pass only listcirclemetrics and listcirclepolicies to keep the agent in a read-only state. This prevents accidental writes to your live GlassFrog organization.

Connect your enterprise Google ADK agents to GlassFrog to manage roles and projects across 1M+ token contexts.

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Connect GlassFrog MCP to Google ADK

Create your Vinkius account to connect GlassFrog 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 GlassFrog with Google ADK

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Analyze complete org structures in Gemini

The `list_holacracy_circles` tool pulls your entire GlassFrog hierarchy into the Gemini 1M+ token context window. This allows your Google ADK agent to reason over every circle simultaneously. You pass the toolset into your Google ADK LlmAgent configuration using the StreamableHttpServerParameters. The agent cross-references this live GlassFrog structure with your enterprise data warehouses.

Map BigQuery records to GlassFrog roles with our MCP Server

The `list_role_assignments` and `list_org_members` tools let you align your internal database with your active GlassFrog roles. Your Google ADK agent queries these tools to find discrepancies. By coupling this GlassFrog MCP Server with Google Cloud datasets, you automate role auditing. The Google ADK agent identifies unassigned roles and matches them to employees based on historical performance data.

Automate tactical project tracking

The `list_tactical_projects` and `list_checklist_items` tools expose the current operational workload of your team to Google ADK. Your agent monitors these lists to generate status reports. You can use the tool_names filter in the Google ADK to expose only these tactical GlassFrog tools. This keeps your agent focused on project execution without exposing governance settings.

Setup guide

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

Install the SDK using pip install google-adk and import McpToolset. Initialize it with StreamableHttpServerParameters pointing to your Vinkius GlassFrog endpoint, then pass it to your Google ADK LlmAgent tools list. This registers all 12 tools instantly.

Yes, you can combine the GlassFrog toolset with your BigQuery tools in a single Google ADK LlmAgent. The agent can read GlassFrog role definitions using list_holacracy_roles and join that data with employee performance metrics stored in Google Cloud.

Use the optional tool_names filter when initializing your Google ADK McpToolset. For example, pass only list_circle_metrics and list_circle_policies to keep the agent in a read-only state. This prevents accidental writes to your live GlassFrog organization.

It supports both Stdio and Streamable HTTP transports. For cloud-hosted Google ADK deployments, the Streamable HTTP transport is the standard choice as it runs without local process management on Vertex AI.

Your GlassFrog projects and checklists pass through isolated memory space that is instantly wiped. This MCP Server handles authentication via Vinkius's zero-trust gateway where your API token is encrypted at rest and never exposed to the LLM.

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