How to Use the Marketaux MCP in AutoGen

Q: How do I load Marketaux tools into AutoGen?

Install autogen-extmcp. Fetch the tools using StreamableHttpServerParams and pass the list directly to your AssistantAgent constructor.

Q: Are my multi-agent debates private?

Vinkius operates entirely on ephemeral infrastructure. The getsentimentanalysis scores and the specific ticker symbols your agents debate vanish immediately after the HTTP response. No persistent storage retains your trading thesis.

Deploy AutoGen agents with Marketaux. Build multi-agent systems that debate financial sentiment and market trends.

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Connect Marketaux MCP to AutoGen

Create your Vinkius account to connect Marketaux 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 Marketaux with AutoGen

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Marketaux MCP Server for AutoGen

This MCP Server equips your AutoGen agents with live financial data. You initialize the tools via `mcp_server_tools` and pass them to your AssistantAgent. The adapter handles all schema conversions automatically. Multiple agents use this data to debate market positions. A risk agent calls `get_stock_market_status` to check for macro volatility, while a momentum agent pulls `get_trending_news`. They argue over conflicting signals and converge on a final decision.

Analyze sentiment through debate

The `get_sentiment_analysis` tool provides the quantitative baseline for agent deliberation. Your quantitative agent pulls the raw sentiment scores. A separate fundamental agent reviews the actual articles. They negotiate the reality of the market. If the sentiment score is high but the `search_news` results show sarcastic or highly volatile reporting language, the fundamental agent challenges the trade. You get consensus-driven execution.

Validate entities across exchanges

Agents use `get_symbols` and `get_entities` to verify ticker validity before executing logic. A compliance agent checks the exact exchange using `search_exchanges`. It blocks any action involving unverified or OTC markets. The `list_industries` and `get_indices` endpoints provide sector context. When a news event hits, your agents map the blast radius across related industries. They build a complete thesis based on hard API data, not assumptions.

Setup guide

Set up Marketaux 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 Marketaux 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="Marketaux_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

Get your connection token →

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="Marketaux_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Marketaux 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 Marketaux. 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.

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Common questions about Marketaux MCP in AutoGen

Install `autogen-ext[mcp]`. Fetch the tools using `StreamableHttpServerParams` and pass the list directly to your AssistantAgent constructor.

Yes. Your group chat can feature three different agents all querying `search_news` with different parameters. They share the results in the conversation thread.

You must build a rate-limit agent or implement strict backoff logic. If `get_latest_news` returns a 429 error, your agent needs explicit instructions to wait.

AutoGen supports both stdio and Streamable HTTP transports. You point the client at the Vinkius URL and the framework handles the connection.

Vinkius operates entirely on ephemeral infrastructure. The `get_sentiment_analysis` scores and the specific ticker symbols your agents debate vanish immediately after the HTTP response. No persistent storage retains your trading thesis.

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