Bring Business Banking
to Pydantic AI
Learn how to connect Mercury to Pydantic AI and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Mercury MCP Server?
Connect your Mercury banking account to any AI agent and manage startup finances through natural conversation.
What you can do
- Account Management — Access balances across all checking and savings accounts
- Transactions — Browse and filter recent transactions and transfers
- Statements — Retrieve monthly account statements
- Cash Flow — Track incoming revenue and outgoing expenses
- Recipient Management — Access saved wire and ACH recipients
How it works
1. Subscribe to this server
2. Enter your Mercury API Token
3. Start managing your finances from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Founders — check runway and cash flow quickly
- Finance Teams — automate transaction categorization and reconciliation
- Developers — build internal financial dashboards
Built-in capabilities (8)
Get details for a specific Mercury account
Get account balance
List Mercury bank accounts
List Mercury debit cards
List invoicing customers
List account receivable invoices
List payment recipients
List transactions for an account
Why Pydantic AI?
Pydantic AI validates every Mercury tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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 Mercury 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 Mercury connection logic from agent behavior for testable, maintainable code
Mercury in Pydantic AI
Mercury and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Mercury 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 | 3,400+ 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 Mercury in Pydantic AI
The Mercury 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 8 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
Mercury for Pydantic AI
Every tool call from Pydantic AI to the Mercury MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I view balances and recent transactions?
Yes. You can query balances for all accounts and list recent incoming/outgoing transactions.
How does Mercury authentication work?
Mercury uses a Bearer token (API Token) against api.mercury.com/api/v1. Tokens must be generated with read-only scopes.
Can I initiate money transfers via the API?
The standard API token allows read-only access to balances and transactions for security reasons.
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 Mercury MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai