How to Use the Intrinio MCP in Pydantic AI

Q: How do I install the Intrinio toolset in Pydantic AI?

Run pip install "pydantic-ai-slimmcp" to get the required dependencies. Then, instantiate the MCP toolset with the Intrinio server HTTP endpoint and pass it to your Pydantic AI agent's toolsets parameter.

Build type-safe financial pipelines with Pydantic AI, validating every Intrinio stock price and financial statement at runtime.

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Connect Intrinio MCP to Pydantic AI

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Setup Intrinio with Pydantic AI

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Type-safe financial analysis with Pydantic AI

Stop worrying about silent data corruption in your quantitative pipelines. When you connect Pydantic AI to Intrinio, every payload returned by `get_financials` or `get_stock_prices` is validated against strict runtime models. If an Intrinio API response changes or returns unexpected nulls, your Pydantic AI code fails immediately instead of executing bad trades. This strict validation is crucial when processing complex Intrinio balance sheets. You can initialize the MCP connection using the toolset with your Intrinio server URL and pass it to your Pydantic AI agent, giving your models a reliable, typed interface to fetch data without custom parsing code.

Validate market events and news feeds

Ensure your Pydantic AI event-driven strategies rely on valid structured Intrinio data. By exposing Intrinio's `get_earnings_releases` and `get_ipo_calendar` to your Pydantic AI agent, you guarantee that date strings, ticker formats, and financial figures match your expected schemas before they reach your decision logic. Your Pydantic AI agent can monitor market sentiment by querying Intrinio's `list_news` and checking the output structure. If the Intrinio news payload contains malformed metadata, the Pydantic AI validation layer catches it instantly, ensuring your natural language processing models only ingest clean text.

Secure instrument discovery using Pydantic AI MCP Server

Resolve Intrinio tickers with absolute structural certainty using Pydantic AI. Your Pydantic AI agent can call Intrinio's `search_companies` to find a business, then run `get_security` to verify the exchange details and asset identifiers. Because every step is strictly validated by Pydantic AI, your agent won't confuse Intrinio class A and class B shares due to loose string matching. The Pydantic AI framework is completely model-agnostic, meaning you can run these validated Intrinio financial tools using OpenAI, Anthropic, or local models. The unified Pydantic AI toolset approach replaces deprecated HTTP classes, making it easy to maintain your Intrinio market discovery pipelines over time.

Setup guide

Set up Intrinio MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "intrinio-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Intrinio tools.",
)

result = await agent.run("List recent Intrinio transactions")
print(result.output)

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Common questions about Intrinio MCP in Pydantic AI

Run pip install "pydantic-ai-slim[mcp]" to get the required dependencies. Then, instantiate the MCP toolset with the Intrinio server HTTP endpoint and pass it to your Pydantic AI agent's toolsets parameter.

Yes, the Pydantic AI framework validates all incoming data from Intrinio tools like get_financials and get_stock_prices at runtime. Any structural mismatch triggers a validation error, preventing corrupt data from entering your calculations.

The framework supports both Streamable HTTP and SSE transports. Use the unified MCPToolset class to connect to your externally running Intrinio MCP Server instance.

Pydantic AI will raise a validation error at runtime. This prevents your agent from making assumptions based on incomplete Intrinio corporate profiles or missing employee counts.

All requests for Intrinio financial statements and stock prices are routed through isolated V8 sandboxes on Vinkius. No data is stored, and the strict schema validation happens entirely in your local Pydantic AI runtime memory, keeping your proprietary trading logic private.

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