Bring Serverless
to Pydantic AI
Learn how to connect Xata to Pydantic AI and start using 28 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 Xata MCP Server?
Connect your Xata account to any AI agent to manage your serverless data infrastructure through natural conversation.
What you can do
- Organization Management — List, create, and update organizations, and manage member invitations and roles.
- Project Control — Create and list projects within your organizations and monitor resource limits and quotas.
- Database Operations — Manage branches, retrieve credentials, and execute SQL queries directly against your data.
- Developer Workflow — Handle API keys and GitHub integrations to streamline your deployment pipeline and repository mapping.
How it works
- Subscribe to this server
- Enter your Xata API Key
- Start managing your databases from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Backend Developers — quickly spin up projects and branches without leaving the terminal or IDE.
- Data Engineers — query data and inspect organization structures via SQL directly through the agent.
- DevOps Managers — automate member access, invite collaborators, and manage API key rotations.
Built-in capabilities (28)
Cancel a pending organization invitation
Create a new database branch
Create an API key for the organization
Create a new Xata organization
Create a new project in an organization
Create a new user API key
Bulk delete user API keys by ID
Execute single or batch SQL queries over HTTP
Retrieve database username and password for a branch
Query observability data (CPU, Memory, Disk, etc.) for a branch
Retrieve the current GitHub repository mapping for a branch
Get detailed information about a specific organization
Get resource limits for projects in an organization
Link a GitHub App installation to an organization
Invite a user to an organization via email
List all branches in a project
List available PostgreSQL versions/images
List organization-scoped API keys
List pending or expired invitations for an organization
List members of an organization
List all organizations the authenticated user belongs to
List all projects within an organization
List available regions for project deployment
List API keys for the authenticated user
Map a GitHub repository to a branch
Remove a member from an organization
Trigger a password rotation for a branch
Update organization information
Why Pydantic AI?
Pydantic AI validates every Xata tool response against typed schemas, catching data inconsistencies at build time. Connect 28 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.
- —
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 Xata integration code
- —
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 Xata connection logic from agent behavior for testable, maintainable code
Xata in Pydantic AI
Xata and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Xata 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 Xata in Pydantic AI
The Xata 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 28 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
Xata for Pydantic AI
Every tool call from Pydantic AI to the Xata MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I see all organizations I have access to?
Yes! Use the list_organizations tool to retrieve all Xata organizations available to your current API key.
How do I start a new project in a specific organization?
Simply use the create_project action providing the organization_id and the desired name for your new project.
Can I run raw SQL queries through the agent?
Yes, the execute_sql tool allows you to run SQL queries directly against your database branches for advanced data manipulation and analysis.
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 Xata 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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