How to Use the Firefish MCP in Google ADK

Connect Google ADK agents to your Firefish recruitment data.

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Connect Firefish MCP to Google ADK

Create your Vinkius account to connect Firefish 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 Firefish with Google ADK

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Enterprise data retrieval with Google ADK

Bridge your recruitment data to your cloud infrastructure. Use `list_companies` and `list_contacts` to bring client details into your Gemini-powered agent. This setup allows the agent to reason over your entire CRM history. It connects your existing data silos into a single, queryable source.

Full placement visibility for Google ADK agents

Track your success rates by exposing `list_placements` to your agent. It monitors closed deals and candidate status updates automatically. Your agent can now report on progress without you running manual exports. It’s a direct window into the current state of your business.

Flexible tool filtering in your MCP Server

Restrict what your agent can see by using the tool name filter. You choose exactly which endpoints like `list_adverts` are exposed to the model. This provides a clean interface for your agent. It only interacts with the specific Firefish tools you authorize for the task.

Setup guide

Set up Firefish 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 Firefish 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="Firefish_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Firefish 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 Firefish. 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.

Why Choose Vinkius

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Common questions about Firefish MCP in Google ADK

Yes, the server provides a standard interface that the ADK consumes via HTTP or Stdio. It integrates right into your existing cloud workflows.

The architecture keeps your data within a private sandbox. Your agent only accesses the information requested through the MCP standard.

You don't need to train the model on the data. The agent queries the CRM live using the provided tools for up-to-the-minute accuracy.

The server is optimized for high-throughput requests. Your agent will receive responses from `list_companies` and other tools in real-time.

It handles structured recruitment entities like candidate profiles, job adverts, and client contact information. Access is strictly controlled via your endpoint.

Use it with your favorite AI tools

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