Compatible with every major AI agent and IDE
What is the PBGC Pension Data MCP Server?
Connect to the PBGC (Pension Benefit Guaranty Corporation) open data repository and empower your AI agent to analyze US pension plan health and regulatory metrics through natural conversation.
What you can do
- Single-Employer Plans — List and filter active plans by EIN, Plan Number, or State to monitor corporate pension landscapes.
- Multiemployer Plans — Retrieve comprehensive lists of active multiemployer plans insured by the PBGC.
- ERISA 4044 Rates — Access critical interest assumptions (select and ultimate rates) used for determining the present value of annuities.
- Financial Assistance — Track and analyze financial assistance payments made by the PBGC to multiemployer plans by fiscal year.
How it works
- Subscribe to this server
- Enter your PBGC Open Data API Key (or public token)
- Start querying pension datasets directly from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Financial Analysts — quickly gather data on pension plan premiums and financial assistance trends.
- Actuaries & Legal Professionals — retrieve ERISA 4044 interest assumptions for valuation and compliance without manual spreadsheet lookups.
- Policy Researchers — analyze the distribution of pension plans across different states and fiscal years.
Built-in capabilities (4)
Get ERISA 4044 Interest Assumptions
List financial assistance payments
List active multiemployer pension plans
List active single-employer pension plans
Why Pydantic AI?
Pydantic AI validates every PBGC Pension Data 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.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your PBGC Pension Data integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your PBGC Pension Data connection logic from agent behavior for testable, maintainable code
PBGC Pension Data in Pydantic AI
PBGC Pension Data and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect PBGC Pension Data to Pydantic AI 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 PBGC Pension Data in Pydantic AI
The PBGC Pension Data 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 Pydantic AI 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
PBGC Pension Data for Pydantic AI
Every tool call from Pydantic AI to the PBGC Pension Data MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I filter single-employer pension plans for a specific state?
You can use the list_single_employer_plans tool and provide the two-letter state code (e.g., 'NY' or 'CA') in the state parameter to get localized results.
Can I retrieve ERISA 4044 interest rates for a specific year and quarter?
Yes! The list_erisa_4044_rates tool accepts optional year and quarter parameters to fetch the exact interest assumptions you need for valuation.
Is it possible to see financial assistance payments by fiscal year?
Absolutely. Use the list_financial_assistance tool and specify the fiscal_year (e.g., 2023) to see all payments made to multiemployer plans during that period.
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 PBGC Pension Data MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai
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