- ClickHouse AI
The open platform for AI on real-time data
Bring AI to your live data with managed agents or your own. Get fast answers at agent scale, with an open stack you control.
Trusted by teams at
Why ClickHouse for AI
Put your agents to work on live data.
Run fast at agent scale
Get sub-second answers over billions of rows, even when agents run thousands of concurrent queries. Keep performance and costs predictable as query volume grows.
Use our agents or bring your own
Start with ClickHouse Agents, powered by Claude, or bring your own agents through MCP. Build and run the workflows you need on the same real-time data engine.
Own your stack and trust every answer
Inspect, extend, and run the open components behind your AI stack. Trace and evaluate agent workflows with Langfuse to improve quality, cost, and latency.
Choose your agents.
Keep control of what you build.
Use managed agents, build your own, or connect the ones you already run. Keep the same fast data foundation across every path.
ClickHouse-managed Agents & AI
Assistant · Agent Builder · Code Interpreter · AI Functions
Bring your own agents
Any agent or framework, over MCP, APIs, CLI & plugins
One ClickHouse platform
Sub-second answers at agent scale.
Powered by open projects and protocols you can run
AgentsPublic beta
Chat with live data and ship agents for every team
ClickHouse Agents is the fully managed agentic analytics service in ClickHouse Cloud, powered by Claude. Ask questions in natural language and get answers, charts, and dashboards from live data, then turn your data team’s expertise into governed agents anyone can use.
- No-code Agent Builder with skills and context files
- Sandboxed code interpreter for Python, JavaScript, and more
- SSO, access controls, and encrypted message storage
ClickHouse Agent
Why did eu-west p95 latency spike on Apr 27? Chart it against the baseline.
- Queried ClickHouse· 6,480 rows
- Ran Python in the code interpreter· 1.8 s
eu = df[df.region == "eu-west"].p95_ms
base = eu[:"2026-04-27 13:00"].median()
peak, at = eu.max(), eu.idxmax()
back = eu[at:][eu[at:] <= 1.15 * base].index[0]
print(round(peak / base, 1), back - at)1,298 ms
baseline 163 ms
Apr 27Apr 28Apr 29
- peak vs baseline
- 8.0×
- to recover
- 13 h
- peak error rate
- 5.9%
AI SQL FunctionsCloud private preview
Put LLMs to work inside your queries
Classify, extract, embed, generate, and translate directly in SQL. AI functions call a language model from any query, so you can enrich, filter, and search text where it already lives, with no pipeline to build and no data to move.
- Embeddings and similarity search with aiEmbed and aiSimilarity
- OpenAI or Anthropic models, configured once as named collections
- Per-query token and API call limits, with retries built in
SQL console
SELECT
body,
aiClassify(
body, ['bug', 'question', 'feature']
) AS kind,
aiExtract(body, 'the product area') AS area
FROM support_tickets
LIMIT 3| body | kind | area |
|---|---|---|
| Dashboard crashes when I filter by date | bug | dashboards |
| How do I rotate my API keys? | question | security |
| Please add CSV export to reports | feature | reports |
MCP
Bring any agent to your ClickHouse data
Connect your agents and tools to live ClickHouse data. Point Claude, Cursor, VS Code, Codex, or your own agent at the ClickHouse Cloud remote MCP server, and it can explore your databases and tables and answer questions with read-only queries.
- One remote endpoint, enabled per service
- OAuth sign-in, or API keys for headless agents
- Open-source MCP server for self-managed ClickHouse
Your agentclickhouse-cloud
What's the average session duration by country for the last 7 days?
- clickhouse-cloud ·list_tables
- clickhouse-cloud ·run_select_query
SELECT country, avg(duration) AS avg_session_s
FROM analytics.sessions
WHERE start_time >= now() - INTERVAL 7 DAY
GROUP BY country
ORDER BY avg_session_s DESC
LIMIT 3- Netherlands412 s
- Germany388 s
- Japan351 s
How it works
Your choice of agents. One data foundation.
Use managed AI or bring your own agents to the same ClickHouse data foundation. Build with shared skills and open connections.
ClickHouse welcomes Langfuse: The future of open-source LLM observability
Built for Production AI
Close the AI engineering loop.
- Trace full agent workflows, from prompts to tool calls and responses
- Evaluate agent outputs with custom scoring and human feedback
- Monitor quality, cost, and latency across every LLM call

Bring AI to your data
Start a free ClickHouse Cloud trial, or run the open-source components yourself. Use our agents or bring your own, and keep control of your stack.
MCP