Tinybird Data Platform MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Tinybird Data Platform through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="Tinybird Data Platform Assistant",
instructions=(
"You help users interact with Tinybird Data Platform. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Tinybird Data Platform"
)
print(result.final_output)
asyncio.run(main())
* 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 Tinybird Data Platform MCP Server
Connect your AI agent to Tinybird, the real-time data platform for developers. This integration allows you to oversee your analytical infrastructure, manage ingestion storage (Data Sources), and interact with transformation logic (Pipes) through natural conversation.
The OpenAI Agents SDK auto-discovers all 10 tools from Tinybird Data Platform through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Tinybird Data Platform, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Infrastructure Oversight — List and inspect all your Data Sources and Pipes in real-time
- Transformation Analysis — Retrieve SQL logic and nodes for any Pipe to understand how data is being processed
- Live Querying — Execute published Pipes or run arbitrary SQL queries (ClickHouse dialect) to explore your data directly via the agent
- Operational Metrics — Check ingestion stats, row counts, and storage sizes for your analytical units
- Access Control — List and audit authentication tokens and workspace configurations
The Tinybird Data Platform 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 Tinybird Data Platform to OpenAI Agents SDK via MCP
Follow these steps to integrate the Tinybird Data Platform 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 Tinybird Data Platform
Why Use OpenAI Agents SDK with the Tinybird Data Platform MCP Server
OpenAI Agents SDK provides unique advantages when paired with Tinybird Data Platform 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
Tinybird Data Platform + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Tinybird Data Platform MCP Server delivers measurable value.
Automated workflows: build agents that query Tinybird Data Platform, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Tinybird Data Platform, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Tinybird Data Platform tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Tinybird Data Platform to resolve tickets, look up records, and update statuses without human intervention
Tinybird Data Platform MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Tinybird Data Platform to OpenAI Agents SDK via MCP:
execute_sql_query
Execute an arbitrary SQL query against the Tinybird workspace
get_datasource_details
Get comprehensive information for a specific Data Source
get_datasource_stats
Retrieve ingestion and usage statistics for a Data Source
get_pipe_details
Get detailed information for a specific Pipe
list_auth_tokens
Retrieve a list of all authentication tokens in the workspace
list_datasources
Retrieve a list of all Data Sources in the current workspace
list_pipe_nodes
List all SQL nodes within a specific Pipe
list_pipes
Retrieve a list of all Pipes in the current workspace
list_workspaces
Retrieve a list of available workspaces
query_pipe_data
Execute a Pipe and retrieve the results as JSON
Example Prompts for Tinybird Data Platform in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Tinybird Data Platform immediately.
"List all data sources in my Tinybird workspace."
"Run the pipe 'monthly_revenue_summary' with limit 5."
Troubleshooting Tinybird Data Platform MCP Server with OpenAI Agents SDK
Common issues when connecting Tinybird Data Platform to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Tinybird Data Platform + OpenAI Agents SDK FAQ
Common questions about integrating Tinybird Data Platform MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
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?
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?
Connect Tinybird Data Platform with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Tinybird Data Platform to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.