How do I find the CIK for a company like Apple?

You can search for a company's CIK on the official SEC website or ask your agent to find it. For Apple, the CIK is '0000320193'. Remember to use the leading zeros if necessary.

Can I see the latest 10-K filing for a specific entity?

Yes! Use the `get_submissions` tool with the company's CIK. The response will list the most recent filings, and you can identify the 10-K report among them.

XBRL (eXtensible Business Reporting Language) is a standardized format for business reporting. It allows the SEC and analysts to extract specific financial facts (like Net Income) from filings programmatically.

SEC EDGAR MCP Server for Pydantic AI 3 tools — connect in under 2 minutes

Name: SEC EDGAR
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 3 Tools SDK

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 EDGAR "
            "(3 tools)."
        ),
    )

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

asyncio.run(main())

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About SEC EDGAR MCP Server

Empower your AI agent with the primary source for US corporate intelligence through the SEC EDGAR MCP server. This integration provides real-time access to the Securities and Exchange Commission's database of public company filings. Your agent can retrieve recent submissions (like annual 10-K and quarterly 10-Q reports), extract specific XBRL financial facts, and audit disclosures for any public entity using its Central Index Key (CIK). Whether you are conducting fundamental analysis, auditing regulatory compliance, or researching corporate history, your agent acts as a dedicated financial analyst through natural conversation.

Pydantic AI validates every SEC EDGAR tool response against typed schemas, catching data inconsistencies at build time. Connect 3 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

Submission Tracking — Retrieve the most recent filings for any public company.
Financial Fact Extraction — Access structured XBRL data for balance sheets, income statements, and more.
Concept Lookup — Fetch company disclosures for specific financial concepts across multiple years.
Entity Identification — Use CIKs to precisely target data for specific public entities.

The SEC EDGAR MCP Server exposes 3 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect SEC EDGAR to Pydantic AI via MCP

Follow these steps to integrate the SEC EDGAR MCP Server with Pydantic AI.

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 3 tools from SEC EDGAR with type-safe schemas

Why Use Pydantic AI with the SEC EDGAR MCP Server

Pydantic AI provides unique advantages when paired with SEC EDGAR 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 EDGAR 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 EDGAR connection logic from agent behavior for testable, maintainable code

SEC EDGAR + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the SEC EDGAR MCP Server delivers measurable value.

Type-safe data pipelines: query SEC EDGAR with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple SEC EDGAR tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query SEC EDGAR and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock SEC EDGAR responses and write comprehensive agent tests

SEC EDGAR MCP Tools for Pydantic AI (3)

These 3 tools become available when you connect SEC EDGAR to Pydantic AI via MCP:

get_company_concept

g., Assets, Liabilities). Get a specific financial concept for a company

get_company_facts

Get financial facts for a company

get_submissions

) for a company using its Central Index Key (CIK). Get recent submissions for a company

Example Prompts for SEC EDGAR in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with SEC EDGAR immediately.

"Get recent submissions for Apple Inc (CIK 0000320193)."

"Extract the 'NetIncomeLoss' for Microsoft (CIK 0000789019) for the last 3 years."

"Find all filings for Tesla (CIK 0001318605) related to '8-K' forms this year."

Troubleshooting SEC EDGAR MCP Server with Pydantic AI

Common issues when connecting SEC EDGAR to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

SEC EDGAR + Pydantic AI FAQ

Common questions about integrating SEC EDGAR 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 EDGAR MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.