How to Use the Xata (Serverless DB) MCP in Pydantic AI

Q: How does Xata (Serverless DB) help monitor database health for Pydantic AI?

You can get performance metrics by calling getbranchmetrics. This gives your agent a real-time view of the branch's operational status. It ensures you know if the system is running efficiently.

Q: Can I list all available branches with Xata (Serverless DB) and Pydantic AI?

Yep, use listbranches. This tool gives your agent a complete directory of every branch within a project. It's crucial for knowing which database connection to target.

Q: What tools are available for Xata (Serverless DB) and Pydantic AI regarding credentials?

Your agent can use getbranchcredentials to read the keys. To prevent stale data, it uses rotatebranchcredentials. This keeps your access tokens fresh without manual intervention.

Q: How do I manage multi-step database changes using Xata (Serverless DB) and Pydantic AI?

Use the executesqlbatch tool. By running queries in a batch, your agent treats them as one transaction block. This guarantees atomicity, which is key for data integrity.

Ensure data correctness: Type-safe database actions with the Pydantic AI framework using MCP Server tools.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Xata (Serverless DB) MCP to Pydantic AI

Create your Vinkius account to connect Xata (Serverless DB) to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Xata (Serverless DB) with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Execute SQL Queries and Validate Data (Pydantic AI)

The `execute_sql` tool lets your agent run specific queries against a database branch. Because of Pydantic validation, if the API sends back unexpected data, your agent fails loud and clear. You get validated results. If you need to modify many records at once, use `execute_sql_batch`. This runs multiple statements in one transaction, ensuring that every output field matches the expected schema.

Manage Project Life Cycles via MCP Server

Your agent controls the entire data structure. It first calls `list_projects` to see available scopes. Then it uses `create_project` to define a new area, or `get_project` to read existing details. If a project is obsolete, the agent handles clean deletion using `delete_project`. This makes managing your data environment predictable.

Control Organization Membership (Pydantic AI)

The server provides tools for user control. Your agent can list all members with `list_members`, and then use `send_invitation` to onboard new users. It also handles removal via `remove_member`. For full lifecycle management, the agent knows how to update details using `update_organization` or even initiate a total cleanup with `request_organization_deletion`.

Setup guide

Set up Xata (Serverless DB) MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "xata-serverless-db-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Xata (Serverless DB) tools.",
)

result = await agent.run("List recent Xata (Serverless DB) transactions")
print(result.output)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Xata. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Xata (Serverless DB) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Xata (Serverless DB) MCP in Pydantic AI

You can get performance metrics by calling `get_branch_metrics`. This gives your agent a real-time view of the branch's operational status. It ensures you know if the system is running efficiently.

Yep, use `list_branches`. This tool gives your agent a complete directory of every branch within a project. It's crucial for knowing which database connection to target.

Your agent can use `get_branch_credentials` to read the keys. To prevent stale data, it uses `rotate_branch_credentials`. This keeps your access tokens fresh without manual intervention.

Use the `execute_sql_batch` tool. By running queries in a batch, your agent treats them as one transaction block. This guarantees atomicity, which is key for data integrity.

It handles organization membership details and project resource limits. Specifically, it manages `list_members` and `get_project_limits`, which are sensitive operational records.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript