QuestDB (Time-Series) MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 4 tools to Execute Sql, Export Data, Import Data, and more

Name: QuestDB (Time-Series)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The QuestDB (Time-Series) MCP Server for OpenAI Agents SDK is a standout in the Databases category — giving your AI agent 4 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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VS Code

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+ other MCP clients

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="QuestDB (Time-Series) Assistant",
            instructions=(
                "You help users interact with QuestDB (Time-Series). "
                "You have access to 4 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from QuestDB (Time-Series)"
        )
        print(result.final_output)

asyncio.run(main())

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About QuestDB (Time-Series) MCP Server

Connect your QuestDB instance to any AI agent to perform high-speed time-series analysis and data management using natural language.

The OpenAI Agents SDK auto-discovers all 4 tools from QuestDB (Time-Series) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries QuestDB (Time-Series), another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

SQL Execution — Run complex SQL queries, DDL, and DML operations optimized for time-series data.
High-Speed Ingestion — Import tabular data (CSV/TSV) directly into tables with automatic schema creation and partitioning.
Data Export — Extract large datasets in CSV or Parquet formats for external analysis or reporting.
Health Monitoring — Instantly check server status and version information to ensure your database is operational.

The QuestDB (Time-Series) MCP Server exposes 4 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 4 QuestDB (Time-Series) tools available for OpenAI Agents SDK

When OpenAI Agents SDK connects to QuestDB (Time-Series) through Vinkius, your AI agent gets direct access to every tool listed below — spanning time-series, sql, data-ingestion, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

execute

Execute sql on QuestDB (Time-Series)

Use this for standard SELECT, INSERT, or DDL operations. Execute SQL statements (queries, DDL, DML) on QuestDB

export

Export data on QuestDB (Time-Series)

Useful for extracting large datasets. Export query results as CSV or Parquet

import

Import data on QuestDB (Time-Series)

Automatically creates tables and columns if they do not exist. Import tabular data (CSV, TSV) into a table

action

Ping on QuestDB (Time-Series)

Health check and version information

Connect QuestDB (Time-Series) to OpenAI Agents SDK via MCP

Follow these steps to wire QuestDB (Time-Series) into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 4 tools from QuestDB (Time-Series)

Why Use OpenAI Agents SDK with the QuestDB (Time-Series) MCP Server

OpenAI Agents SDK provides unique advantages when paired with QuestDB (Time-Series) 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

QuestDB (Time-Series) + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the QuestDB (Time-Series) MCP Server delivers measurable value.

Automated workflows: build agents that query QuestDB (Time-Series), process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries QuestDB (Time-Series), another analyzes results, a third generates reports

Data enrichment pipelines: stream data through QuestDB (Time-Series) tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query QuestDB (Time-Series) to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for QuestDB (Time-Series) in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with QuestDB (Time-Series) immediately.

"Check if the QuestDB server is online and show me the version."

"Execute a query to find the average temperature from the 'sensors' table for the last hour."

"Export the last 1000 rows of the 'trades' table as a CSV file."

Troubleshooting QuestDB (Time-Series) MCP Server with OpenAI Agents SDK

Common issues when connecting QuestDB (Time-Series) to OpenAI Agents SDK through 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.

QuestDB (Time-Series) + OpenAI Agents SDK FAQ

Common questions about integrating QuestDB (Time-Series) 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.

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.

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