Can I run destructive commands like deleting databases through this AI implementation?

Yes. The integration provides `delete_branch` and `delete_database`. They map directly to infrastructure teardowns. You should scope the Service Token carefully inside the PlanetScale dashboard to avoid catastrophic misinterpretations if your explicit intent is just testing. Deletions via `delete_database` are absolute and irretrievable.

Does `create_branch` replicate and copy my production dataset into the new branch?

No. PlanetScale branches solely duplicate the static underlying DDL structure (schema), exactly like taking a snapshot of empty tables. The new branch boots up free of rows. This design lets your agent freely run `ALTER TABLE` operations independently without crashing the master tables.

How does the agent know which organizational node I am provisioning my branches on?

All queries essentially require the foundational string parameters known as the `org_name`. If unknown, a simple `list_organizations` query reveals the UUID scope dictating your authorized account parameter bounds securely.

PlanetScale MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: PlanetScale
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect PlanetScale through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="PlanetScale Assistant",
            instructions=(
                "You help users interact with PlanetScale. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from PlanetScale"
        )
        print(result.final_output)

asyncio.run(main())

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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

About PlanetScale MCP Server

Empower your AI agents to manage your PlanetScale serverless infrastructure seamlessly. Leverage the power of Vitess-backed MySQL without leaving your IDE. Ask your AI to branch a production database for testing, list regions, or drop obsolete schema forks instantly.

The OpenAI Agents SDK auto-discovers all 10 tools from PlanetScale through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries PlanetScale, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Database Provisioning — Instantly list (list_databases), inspect, create (create_database), or destroy serverless MySQL clusters running across global regions.
Branch Management — Harness PlanetScale's Git-like schema workflows. Direct your LLM to spawn a temporary shadow-test branch cloned from main (create_branch), allowing consequence-free migrations before orchestrating Deploy Requests.
Infrastructure Exploration — Discover strict organizational IDs (list_organizations) and query available physical cloud provider edges (list_regions) to optimize latency targets.

The PlanetScale MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect PlanetScale to OpenAI Agents SDK via MCP

Follow these steps to integrate the PlanetScale MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from PlanetScale

Why Use OpenAI Agents SDK with the PlanetScale MCP Server

OpenAI Agents SDK provides unique advantages when paired with PlanetScale through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

PlanetScale + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the PlanetScale MCP Server delivers measurable value.

Automated workflows: build agents that query PlanetScale, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries PlanetScale, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through PlanetScale tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query PlanetScale to resolve tickets, look up records, and update statuses without human intervention

PlanetScale MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect PlanetScale to OpenAI Agents SDK via MCP:

create_branch

Does *not* duplicate data (creates an empty schema clone of the parent) for secure CI testing uncoupled entirely from `main` load balancing layers. Fork a PlanetScale schema mapping to a new isolated Branch

create_database

Creates empty environments ready to execute explicit DDL definitions via non-blocking Deploy Requests. Provision a radically scalable Serverless Database instance

delete_branch

Utilized constantly within CI/CD pipelines following a successful Deploy Request morphing `main` schema structure directly. Purge an obsolete Git-like Schema testing ground

delete_database

Dropping the database effectively wipes terabytes of records scattered globally. Fails fully if unacknowledged connection logic binds it. Destroy a PlanetScale MySQL construct irreversibly

get_branch

Returns access hostnames for code integration. Deconstruct the layout of a single explicit Database Branch

get_database

Analyze core configuration of a specific MySQL cluster logic

list_branches

Essential for migrating schemas without locking production reads/writes. List Development Database Branches mirroring Prod architectures

list_databases

Retrieves explicitly mapping IDs orchestrating distributed Vitess backend shards. List high-availability PlanetScale MySQL DB distributions

list_organizations

Used solely to resolve the foundational string key prerequisite for all subsequent MySQL endpoint management. List root PlanetScale organizational identifiers

list_regions

Critical reference required during new Database/Branch physical provisioning routines. Locate physical edge availability zones supported by Vitess

Example Prompts for PlanetScale in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with PlanetScale immediately.

"List all physical cloud regions currently exposed by the PlanetScale integration."

"We're starting a new feature. Fork testing branch from the main database 'store-backend'."

"Drop the specific 'staging-01' branch inside the 'web-portal' database."

Troubleshooting PlanetScale MCP Server with OpenAI Agents SDK

Common issues when connecting PlanetScale to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

PlanetScale + OpenAI Agents SDK FAQ

Common questions about integrating PlanetScale MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.