SEC XBRL (Financial Reporting) MCP Server for Pydantic AIGive Pydantic AI instant access to 4 tools to Get Company Concept, Get Company Facts, Get Submissions, and more

Name: SEC XBRL (Financial Reporting)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect SEC XBRL (Financial Reporting) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The SEC XBRL (Financial Reporting) MCP Server for Pydantic AI is a standout in the Data Management category — giving your AI agent 4 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to SEC XBRL (Financial Reporting) "
            "(4 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in SEC XBRL (Financial Reporting)?"
    )
    print(result.data)

asyncio.run(main())

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About SEC XBRL (Financial Reporting) MCP Server

Connect your AI agent to the SEC EDGAR database and perform deep financial analysis using standardized XBRL data. This server provides programmatic access to the U.S. Securities and Exchange Commission's public filing infrastructure.

Pydantic AI validates every SEC XBRL (Financial Reporting) tool response against typed schemas, catching data inconsistencies at build time. Connect 4 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Filing History — Retrieve the complete submission history for any entity using its Central Index Key (CIK)
Company Facts — Fetch the entire dictionary of XBRL facts reported by a company, covering all taxonomies (US-GAAP, IFRS, etc.)
Concept Analysis — Drill down into specific financial concepts (e.g., Net Income, Assets) for a single company over time
Market-Wide Frames — Aggregate specific financial data points across all reporting entities for a particular period and unit

The SEC XBRL (Financial Reporting) MCP Server exposes 4 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 4 SEC XBRL (Financial Reporting) tools available for Pydantic AI

When Pydantic AI connects to SEC XBRL (Financial Reporting) through Vinkius, your AI agent gets direct access to every tool listed below — spanning xbrl, financial-reporting, sec-edgar, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get company concept on SEC XBRL (Financial Reporting)

Get all XBRL disclosures for a single company concept

get

Get company facts on SEC XBRL (Financial Reporting)

Get all company concepts data for a specific company

get

Get submissions on SEC XBRL (Financial Reporting)

Includes metadata and recent filings. Get filing history for a specific entity

get

Get xbrl frames on SEC XBRL (Financial Reporting)

Get aggregated facts for a specific concept and period

Connect SEC XBRL (Financial Reporting) to Pydantic AI via MCP

Follow these steps to wire SEC XBRL (Financial Reporting) into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 4 tools from SEC XBRL (Financial Reporting) with type-safe schemas

Why Use Pydantic AI with the SEC XBRL (Financial Reporting) MCP Server

Pydantic AI provides unique advantages when paired with SEC XBRL (Financial Reporting) through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your SEC XBRL (Financial Reporting) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your SEC XBRL (Financial Reporting) connection logic from agent behavior for testable, maintainable code

SEC XBRL (Financial Reporting) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the SEC XBRL (Financial Reporting) MCP Server delivers measurable value.

Type-safe data pipelines: query SEC XBRL (Financial Reporting) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple SEC XBRL (Financial Reporting) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query SEC XBRL (Financial Reporting) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock SEC XBRL (Financial Reporting) responses and write comprehensive agent tests

Example Prompts for SEC XBRL (Financial Reporting) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with SEC XBRL (Financial Reporting) immediately.

"Get the filing history for Microsoft using CIK 789019."

"Show me all XBRL facts reported by Apple (CIK 320193)."

"Compare the 'AccountsPayableCurrent' for all companies in USD for the period CY2023Q3."

Troubleshooting SEC XBRL (Financial Reporting) MCP Server with Pydantic AI

Common issues when connecting SEC XBRL (Financial Reporting) to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

SEC XBRL (Financial Reporting) + Pydantic AI FAQ

Common questions about integrating SEC XBRL (Financial Reporting) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your SEC XBRL (Financial Reporting) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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