How to Use the Intrinio MCP in AutoGen

Q: How do I register the Intrinio MCP Server with AutoGen agents?

Install the autogen-ext package and use the mcpservertools function with your Vinkius server URL. Pass the resulting tool list directly into your AssistantAgent constructor.

Q: Can AutoGen agents share Intrinio tool outputs during a conversation?

Yes, the agents pass tool outputs like the results of getfinancials back and forth in their chat history. This allows the entire group to analyze the same dataset.

Let AutoGen agents debate market trends using real-time Intrinio stock data and financial statements.

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Connect Intrinio MCP to AutoGen

Create your Vinkius account to connect Intrinio 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 Intrinio with AutoGen

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Consensus-driven financial analysis in AutoGen

Build a team of agents that discuss market data before making a call. One agent can pull historical data using `get_stock_prices` while another pulls corporate profiles with `get_company` to debate valuation. By using this MCP Server, your agents negotiate based on actual financial facts. They can cross-reference `get_financials` with recent news to reach a verified consensus.

Multi-agent coordination with AutoGen and MCP

Coordinate complex tasks across specialized agents. Let a research agent use `search_companies` to locate a ticker, while an analyst agent uses `get_security` to verify the instrument type. This division of labor prevents rate-limit exhaustion. Agents only trigger tools like `get_earnings_releases` when the group consensus demands it, keeping API usage efficient.

Real-time market monitoring teams

Set up dedicated agents to monitor market developments. One agent can watch `list_news` for breaking announcements, while a second agent tracks index performance via `list_indices`. The MCP Server handles the underlying connection, allowing agents to immediately query the IPO calendar using `get_ipo_calendar` to assess the broader market impact and log the results.

Setup guide

Set up Intrinio 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 Intrinio 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="Intrinio_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Intrinio 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="Intrinio_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Intrinio 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 Intrinio. 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 Intrinio MCP in AutoGen

Install the autogen-ext package and use the mcp_server_tools function with your Vinkius server URL. Pass the resulting tool list directly into your AssistantAgent constructor.

Yes, the agents pass tool outputs like the results of `get_financials` back and forth in their chat history. This allows the entire group to analyze the same dataset.

Vinkius manages the connection and authentication details on its side. You only need to provide the single endpoint token to your AutoGen client setup.

It supports both stdio and Streamable HTTP transports. For hosted Vinkius servers, you will typically use the Streamable HTTP client configuration.

Vinkius uses zero-trust, ephemeral sandboxes to execute each tool call. The server only handles financial metrics and ticker symbols, ensuring your private conversation logs and agent prompts are never exposed.

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