Bring Xbrl
to OpenAI Agents SDK
Learn how to connect SEC XBRL (Financial Reporting) to OpenAI Agents SDK and start using 4 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the 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.
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
How it works
- Subscribe to this server
- Enter your SEC User-Agent string (required by SEC Fair Access policy)
- Start querying financial statements from Claude, Cursor, or any MCP client
Who is this for?
- Financial Analysts — instantly pull raw XBRL data for modeling without manual spreadsheet entry
- Investors — monitor recent filings and compare metrics across industries using standardized frames
- Compliance Officers — verify submission histories and disclosure accuracy for specific CIKs
Built-in capabilities (4)
Get all XBRL disclosures for a single company concept
Get all company concepts data for a specific company
Includes metadata and recent filings. Get filing history for a specific entity
Get aggregated facts for a specific concept and period
Why OpenAI Agents SDK?
The OpenAI Agents SDK auto-discovers all 4 tools from SEC XBRL (Financial Reporting) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries SEC XBRL (Financial Reporting), another analyzes results, and a third generates reports, all orchestrated through Vinkius.
- —
Native MCP integration via
MCPServerSse, pass the URL and the SDK auto-discovers all tools with full type safety - —
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
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Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
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First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
SEC XBRL (Financial Reporting) in OpenAI Agents SDK
SEC XBRL (Financial Reporting) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect SEC XBRL (Financial Reporting) to OpenAI Agents SDK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for SEC XBRL (Financial Reporting) in OpenAI Agents SDK
The SEC XBRL (Financial Reporting) MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 4 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in OpenAI Agents SDK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
SEC XBRL (Financial Reporting) for OpenAI Agents SDK
Every tool call from OpenAI Agents SDK to the SEC XBRL (Financial Reporting) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I find the filing history for a specific company?
Use the get_submissions tool with the company's Central Index Key (CIK). For example, Apple is 320193. The tool automatically handles leading zeros.
Can I retrieve specific financial metrics like 'Net Income' for a company?
Yes. Use get_company_concept by providing the CIK, the taxonomy (usually 'us-gaap'), and the XBRL tag (like 'NetIncomeLoss').
How can I compare a single metric across all companies for a specific year?
Use the get_xbrl_frames tool. You can specify a concept, unit, and period (e.g., 'CY2023') to get data for every reporting entity in that timeframe.
How does the OpenAI Agents SDK connect to MCP?
Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.
Can I use multiple MCP servers in one agent?
Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.
Does the SDK support streaming responses?
Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.
MCPServerStreamableHttp not found
Ensure you have the latest version: pip install --upgrade openai-agents
Agent not calling tools
Make sure your prompt explicitly references the task the tools can help with.
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