Bring Terraform
to Pydantic AI
Learn how to connect Infracost to Pydantic AI and start using 13 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 Infracost MCP Server?
Connect Infracost to your AI agent to bring financial visibility and governance to your Infrastructure as Code (IaC) workflows. Prevent cloud cost surprises before they happen.
What you can do
- Cost Guardrails — List, create, and manage guardrails that trigger alerts or block Pull Requests when cost increases exceed your defined thresholds.
- Tagging Governance — Enforce organizational standards by updating tagging policies, ensuring all cloud resources are correctly attributed to departments or projects.
- Custom Pricing — Manage enterprise-specific price books for AWS and Azure to ensure cost estimates reflect your actual negotiated discounts.
- Business Context — Upload custom properties from external systems like ServiceNow or Backstage to map cloud costs to your internal organizational hierarchy.
- Pricing Queries — Programmatically query cloud pricing data to compare costs across different resource types and regions.
How it works
- Subscribe to this server
- Enter your Infracost API Token
- Start managing your cloud governance from Claude, Cursor, or any MCP-compatible client
Who is this for?
- DevOps Engineers — automate the enforcement of cost policies and tagging standards directly within the CI/CD flow.
- FinOps Teams — gain real-time visibility into infrastructure spend and manage custom enterprise discounts without manual spreadsheets.
- Engineering Managers — set budget thresholds and receive automated summaries of cost impacts for proposed infrastructure changes.
Built-in capabilities (13)
Create a new guardrail
Create a custom price book for an enterprise
Delete a guardrail
Get a specific guardrail by ID
Poll this to wait for SUCCESS status. Get the status and details of a price book
Use the returned URL to PUT the CSV file. Get a presigned URL to upload a price book CSV
Call this after uploading the CSV to the presigned URL. Trigger ingestion of an uploaded price book CSV
List all guardrails for an organization
Provide a valid GraphQL query string. Query the Cloud Pricing API using GraphQL
Update an existing guardrail
Pass the customPriceBookId to activate it. Update organization settings, such as activating a custom price book
Update allowed tag values for a tagging policy
g., from ServiceNow or Backstage) for cost attribution. Provide raw CSV data. Upload custom business properties via CSV
Why Pydantic AI?
Pydantic AI validates every Infracost tool response against typed schemas, catching data inconsistencies at build time. Connect 13 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 Infracost 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 Infracost connection logic from agent behavior for testable, maintainable code
Infracost in Pydantic AI
Infracost and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Infracost 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 Infracost in Pydantic AI
The Infracost 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 13 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
Infracost for Pydantic AI
Every tool call from Pydantic AI to the Infracost 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 see all active cost guardrails for my organization?
You can use the list_guardrails tool by providing your organization slug. The agent will return a list of all configured thresholds, including cost increase limits and whether they block PRs.
Can I enforce mandatory tags for my cloud resources using this server?
Yes! Use the update_tagging_policy tool to define mandatory tag keys and allowed values. This helps maintain standards across all your repositories.
Is it possible to block expensive Pull Requests automatically?
Absolutely. When using create_guardrail or update_guardrail, you can set the blockPr parameter to true. This ensures that any infrastructure change exceeding your budget cannot be merged without review.
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 Infracost MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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