Data Platform
Managed ClickHouse®
Production-ready with Tinybird's DX
Streaming ingestion
High-throughput streaming ingest
Schema iteration
Safe migrations with zero downtime
Connectors
Plug and play Kafka, S3, and GCS
The analytics backend for your app and agents
Tinybird is the real-time analytics platform for the agentic era. Learn more about Tinybird Code, the Tinybird MCP Server, the Explorations UI, and how to build your own autonomous analytics agents.
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Tinybird Code is the AI expert for ClickHouse® database software
Tinybird’s mission is to simplify operating ClickHouse in production to give developers tools they love to work with large amounts of data at any scale.
[02]
Tinybird Agent Skills
Best practices for your AI coding agent
Install Tinybird's official skill pack to help your AI coding agent build optimized datasources, pipes, and endpoints following Tinybird Engineering's best practices.
[View on GitHub]//--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------//
# Install Tinybird Agent Skills
npx skills add tinybirdco/tinybird-agent-skills[03]
Tinybird MCP
Your real‑time data, LLM‑ready
A remote, hosted MCP server that allows your AI agents to connect directly to your Tinybird workspace.
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Your Tinybird workspaces
as remote MCPs
Instantly connect LLMs and agents to any Tinybird workspace. Tinybird's fully managed, hosted MCP server gives you everything you need to expose your data and APIs as LLM tools—no setup, no ops, zero friction.
// Get your TB_TOKEN from https://cloud.tinybird.co/tokens
// Configure your client with the Tinybird MCP server URL and a token
{
"mcpServers":{
"tinybird":{
"url":"https://mcp.tinybird.co?token=TB_TOKEN"
}
}
}Advanced Data Tools, Out‑of‑the‑Box
Tinybird's hosted MCP server exposes convenient tools for agents to successfully and efficiently explore Tinybird data
from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.mcp import MCPTools
import asyncio
import os
tinybird_api_key = os.getenv("TINYBIRD_TOKEN")
tinybird_host = os.getenv("TINYBIRD_HOST")
async def main():
async with MCPTools(
transport="streamable-http",
url=f"https://mcp.tinybird.co?token={tinybird_api_key}&host={tinybird_host}",
timeout_seconds=120) as mcp_tools:
agent = Agent(model=Claude(id="claude-4-opus-20250514"), tools=[mcp_tools])
await agent.aprint_response("top 5 pages with more visits in the last 24 hours", stream=True)
if __name__ == "__main__":
asyncio.run(main())>> Output
No Data Leakage
MCP never exposes more than the underlying credentials allow.
/ 01
Access Control Built In
Tinybird MCP leverages your existing Tinybird static tokens and JWTs.
/ 02
RBAC for your MCPs
Give precise access with row-level authorization.
Built in observability
Every tool call is tracked and stored in Tinybird service data sources, so you have detailed observability about how AI is using your resources.
Works with Cursor, clients, and SDKs
Any agent, IDE, or client SDK can interact with Tinybird via Streamable HTTP.
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Explorations
A natural language exploratory data analysis UI to help you understand the shape of your data.
Query your data with natural language
Dig into your data without knowing its schema. Tinybird has all the context to write SQL that answers your questions.
Explore iteratively
Tinybird retains the context from your chat, so you can perform exploratory data analysis interactively and iteratively.
Auto-generated results, analysis and charts
When prompted, Explorations generates timeseries visualizations to help you understand how your data is evolving.
[05]
LLM SQL benchmark
We assessed the ability of popular LLMs to generate accurate and efficient SQL from natural language prompts using a 200 million record dataset from the GitHub Archive.
Tinybird is the data platform for real‑time agentic analytics
