How to Use the Turso MCP in Pydantic AI

Q: What tools should I use to track all libSQL instances in Pydantic AI?

Use listdatabases to get the complete registry. You can complement this by running getdatabasedetails on any specific database for its architectural traits.

Q: Can I audit physical locations using Turso with Pydantic AI?

Yes, listedgelocations gives you a lookup for all global Fly.io datacenter mappings. This helps you understand the physical redundancy of your data.

Q: What happens if I try to delete a database with Pydantic AI?

The deletedatabase tool is irreversible, and Pydantic's strong typing forces you to confirm all necessary parameters before execution. Treat it like the final word.

Type-safe database management for Pydantic AI using Turso MCP Server tools.

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Connect Turso MCP to Pydantic AI

Create your Vinkius account to connect Turso 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.

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Setup Turso with Pydantic AI

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Create and scope databases

The `create_database` tool lets you provision a distributed SQLite server, requiring the organization slug, DB name, and target group. Because of Pydantic's validation, you'll know immediately if any input parameters are wrong.

List all available database groups

Need to see where your data is logically grouped? Call `list_database_groups` to get the overview. This list helps ensure your agent targets the correct operational scope before executing any changes.

Manage and revoke tokens

You can manage access credentials using `list_database_tokens`. If a token is outdated, running `rotate_database_tokens` revokes all existing ones for that DB. The strict typing ensures the right parameters are passed.

Setup guide

Set up Turso 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": {
        "turso-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Turso transactions")
print(result.output)

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Common questions about Turso MCP in Pydantic AI

Pydantic validates every single response from the MCP Server tool, like `list_organizations`. If Turso sends back unexpected fields, your agent fails loudly with a validation error—no silent corruption.

Use `list_databases` to get the complete registry. You can complement this by running `get_database_details` on any specific database for its architectural traits.

The server handles organization slugs, DB names, and connection tokens. Since the tool calls must adhere to a strict schema, it forces explicit handling of sensitive JWT Tokens.

Yes, `list_edge_locations` gives you a lookup for all global Fly.io datacenter mappings. This helps you understand the physical redundancy of your data.

The `delete_database` tool is irreversible, and Pydantic's strong typing forces you to confirm all necessary parameters before execution. Treat it like the final word.

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