How to Use the Anthropic Alternative MCP in Google ADK

Q: Can I use Anthropic Alternative alongside BigQuery data in Google ADK?

Absolutely. You can pipe your BigQuery output into the sendmessage tool. It processes the raw text just like any other input.

Use the Google ADK to bridge your enterprise data with external Claude models.

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Connect Anthropic Alternative MCP to Google ADK

Create your Vinkius account to connect Anthropic Alternative 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 Anthropic Alternative with Google ADK

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Message orchestration for Google ADK

Send your structured data directly to the API using `send_message`. It handles your system prompts and temperature settings to keep your output consistent. This works perfectly alongside your existing Gemini workflows. Just swap the toolset in your LlmAgent configuration.

Batch control for Google ADK

Large scale tasks often require batching to save overhead. Use `create_batch_message` to submit jobs, then check their status with `get_batch_message`. If a job is running too long or the parameters look wrong, `cancel_batch_message` stops the execution immediately. This keeps your Google Cloud environment clean.

Model discovery for Google ADK

Check current model availability with `list_models`. It returns every active model ID you need for your agent calls. Use `count_tokens` before you execute to ensure your prompt fits the context window. It prevents errors before they happen.

Setup guide

Set up Anthropic Alternative 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 Anthropic Alternative 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="Anthropic Alternative_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Anthropic Alternative tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Anthropic Alternative MCP in Google ADK

You initialize a McpToolset with your server URL. Add this toolset to your agent's tool list and you are ready to go.

It supports both Stdio and HTTP transports for your connection. This ensures your agent stays fast even when handling large responses.

It is built to run as a separate service. You can restrict which tools the agent uses by setting a tool_names filter in your config.

We keep your message history in memory only during the active request. Your data never touches our persistent storage.

Absolutely. You can pipe your BigQuery output into the `send_message` tool. It processes the raw text just like any other input.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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