How to Use the Fireworks AI MCP in Google ADK

Bring Fireworks AI model performance to your Google ADK agent framework.

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Connect Fireworks AI MCP to Google ADK

Create your Vinkius account to connect Fireworks AI 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 Fireworks AI with Google ADK

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Perplexity

Gemini-compatible toolset for Google ADK

Integrate the `chat` and `completion` tools into your Google ADK agent. You maintain your existing infrastructure while adding high-speed inference to your workflow. This approach lets you switch models using `list_models`. It keeps your agent flexible when you need to swap between different open-weight versions for specific reasoning tasks.

Audio and visual processing

Turn your agents into multimodal powerhouses with the `image` and `transcribe` tools. You can trigger generation or transcription directly from your agent's control loop. These tools talk to the API endpoints and return results to your ADK agent. It keeps your code clean and focused on business logic rather than API plumbing.

Efficient vector generation

Generate embeddings for your BigQuery data using the `embed` tool. It provides the numerical representation your agent needs to perform semantic search. This fits right into your existing Google Cloud architecture. You process data in real-time, feeding the results back into your agent's long-context window.

Setup guide

Set up Fireworks AI 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 Fireworks AI 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="Fireworks AI_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Fireworks AI 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 Fireworks AI. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Fireworks AI now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Fireworks AI MCP in Google ADK

Absolutely. The server is built to handle the scale required for enterprise deployments. You just configure the `McpToolset` and pass it to your `LlmAgent`.

The server supports both Stdio and HTTP transports, making it compatible with the Google ADK setup. You can restrict which tools are exposed by using a simple tool name filter.

It provides a faster inference alternative for your agents. You can offload specific tasks to these tools while keeping your primary reasoning on Gemini models.

The server acts as a pass-through for your requests. Your sensitive data stays between your agent and the model provider, with no persistent storage on the Vinkius hosting layer.

You can monitor the MCP traffic within your local development environment. Each request is logged according to the standard MCP protocol, showing exactly what input reached the model.

Use it with your favorite AI tools

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

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