How to Use the Glama MCP in Google ADK

Q: How does Glama integrate with the Google ADK toolset?

Provide the Glama HTTP URL to the McpToolset class. This allows your LlmAgent to register and call tools directly from your Google Cloud infrastructure.

Q: Can I use Glama and Google ADK to fetch private instances?

Yes. Call glamagethostedinstances to list your private servers. This ensures your agent only interacts with the infrastructure you have explicitly authorized.

Q: Is model list discovery possible with Glama and Google ADK?

Absolutely. Use glamagetgatewaymodels to retrieve the current model inventory. Your agent then dynamically selects the best gateway model for its Google Cloud queries.

Q: Does the server support telemetry for Google ADK agents?

Yes, trigger glamasendtelemetry to log execution data. This helps you track how often your agents invoke external tools during long-context reasoning sessions.

Bridge your Google ADK enterprise agents to the Glama registry for high-performance model routing.

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Connect Glama MCP to Google ADK

Create your Vinkius account to connect Glama 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 Glama with Google ADK

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Access Glama tools in Google ADK

Configure your `McpToolset` using the Glama endpoint to expose directory tools to your Gemini-powered agents. This links your cloud environment to the global server list. Call `glama_list_mcp_servers` to identify relevant tools for your current task. Your agent gains the ability to find and bind these servers at runtime.

Proxy model requests through Glama

Use `glama_run_gateway_chat` to send prompts through the unified proxy. It bridges your Google Cloud data with external intelligence networks. Verify model constraints with `glama_get_gateway_model_details` before execution. This prevents your agents from hitting context limits during complex enterprise reasoning tasks.

Audit server info for Google ADK

Pull metadata with `glama_get_mcp_server_info` to ensure your agent understands the installation parameters. It prevents configuration drift in your production deployments. Use `glama_get_mcp_attributes` to categorize servers by capability. This keeps your agent toolset clean and relevant to your specific business logic.

Setup guide

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

Provide the Glama HTTP URL to the `McpToolset` class. This allows your `LlmAgent` to register and call tools directly from your Google Cloud infrastructure.

Yes. Call `glama_get_hosted_instances` to list your private servers. This ensures your agent only interacts with the infrastructure you have explicitly authorized.

Absolutely. Use `glama_get_gateway_models` to retrieve the current model inventory. Your agent then dynamically selects the best gateway model for its Google Cloud queries.

Yes, trigger `glama_send_telemetry` to log execution data. This helps you track how often your agents invoke external tools during long-context reasoning sessions.

The server transmits your agent queries through an encrypted proxy channel. It requires a specific endpoint token to access your account, keeping your private business data isolated from public traffic.

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