How to Use the Fireworks AI MCP in AutoGen

Q: How do AutoGen agents share access to the Fireworks AI tools?

You register the server tools using mcpservertools and pass the list to your agent configuration. Every agent in your AutoGen group chat can then call tools like image or chat based on their role instructions.

Q: Can an AutoGen critic agent verify images generated by Fireworks AI?

Yes, a designer agent can generate an image using the image tool and pass the resulting URL to a critic agent. The critic can then analyze the output and request modifications in the next turn of the chat.

Q: How does AutoGen handle schema conversion for Fireworks AI tools?

The McpToolAdapter automatically translates the MCP Server schemas into the format AutoGen expects. This ensures that tools like transcribe and embed work out of the box with zero manual schema definition.

Build debating AutoGen agents that execute Fireworks AI image generation and text completions in parallel.

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Connect Fireworks AI MCP to AutoGen

Create your Vinkius account to connect Fireworks AI to AutoGen 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 AutoGen

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Power AutoGen debates with fast Fireworks AI tools

AutoGen agents need to talk, argue, and verify facts quickly, which means slow APIs will kill your team's momentum. Hooking up this MCP Server gives your debating agents instant access to `chat` and `completion` tools, allowing them to iterate on ideas in real time. While one agent drafts a response, a critic agent can immediately analyze the draft using the same model endpoints. This rapid back-and-forth conversation stays fast because the underlying API is built for speed.

Delegate media tasks to specialized AutoGen agents

You can assign specific tasks like transcription or image generation to dedicated agents in your group chat. A designer agent can call the `image` tool to create visual layouts, while a transcriber agent handles audio inputs using `transcribe`. Because the tools are registered globally across the group, agents can hand off tasks to each other without losing context. The output of an audio transcription can be passed to a writer agent for summary without any manual intervention.

Let agents dynamically discover and switch models

Hardcoding models limits your agents' ability to adapt to complex tasks. By exposing the `list_models` tool, your coordinator agent can inspect available endpoints and assign cheaper models to simple tasks while reserving heavy models for complex reasoning. Agents can also use the `embed` tool to compute semantic similarity during their deliberation phase. This helps them determine if they have reached consensus or if they need to continue debating.

Setup guide

Set up Fireworks AI MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Fireworks AI tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Fireworks AI_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Fireworks AI data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Fireworks AI_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Fireworks AI data")
    print(result.messages[-1].content)

Get your connection token →

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.

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Common questions about Fireworks AI MCP in AutoGen

You register the server tools using `mcp_server_tools` and pass the list to your agent configuration. Every agent in your AutoGen group chat can then call tools like `image` or `chat` based on their role instructions.

Yes, a designer agent can generate an image using the `image` tool and pass the resulting URL to a critic agent. The critic can then analyze the output and request modifications in the next turn of the chat.

The `McpToolAdapter` automatically translates the MCP Server schemas into the format AutoGen expects. This ensures that tools like `transcribe` and `embed` work out of the box with zero manual schema definition.

Yes, you can connect your agents using either transport method. Most developers prefer the HTTP transport using the managed Vinkius URL for easier multi-agent scaling.

Your image prompts and dimension settings are processed in a secure, sandboxed V8 sandbox that is wiped clean the millisecond your request finishes. Your connection is locked down using token-based authentication, keeping your API endpoints secure.

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