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Improvado's MCP server gives your AI agent a direct line into ClickHouse. Write queries, explore schemas, debug slow SQL, and surface insights from your data warehouse — all in plain English. Works with Claude, Cursor, and any MCP-compatible tool.
Your AI agent becomes a fluent ClickHouse analyst. Describe what you want in plain English — the MCP server generates optimized SQL, executes it, and returns structured results. Schema exploration included.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Schema migrations, table creation, data inserts — your AI agent handles them through natural language. Describe the structure you need, confirm the generated DDL, and let the MCP server execute it.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Your AI agent watches ClickHouse for slow queries, replication lag, disk pressure, and table growth anomalies. Get notified before performance degrades or storage runs out.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Schema migrations, table creation, data inserts — your AI agent handles them through natural language. Describe the structure you need, confirm the generated DDL, and let the MCP server execute it.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
Every analyst question that requires ClickHouse becomes an engineering ticket. 'How many users triggered event X in region Y last quarter?' requires knowing table schemas, writing valid SQL, and understanding ClickHouse's dialect. The bottleneck is permanent.
Improvado's MCP server lets AI agents translate plain-English questions into optimized ClickHouse SQL automatically. Analysts ask in natural language — the agent queries, returns results, and explains them. Engineering ticket queue shrinks.
ClickHouse tables get added and modified constantly. Column documentation lives in a Notion page nobody updates. New analysts spend hours reverse-engineering schemas from query examples and asking senior engineers what fields mean.
The MCP server exposes live ClickHouse schema introspection. Your AI agent can describe any table, explain column types and sample values, and even infer business meaning from naming patterns — always reflecting the current state.
A dashboard query is taking 45 seconds. You know it's slow, but diagnosing why requires knowing ClickHouse internals: which indexes are used, whether the ORDER BY matches the table's primary key, if there's a full table scan happening. Most team members don't have that expertise.
Paste the slow query into your AI agent. The MCP server fetches the query plan and table schema, and the agent explains exactly what's causing the slowdown — in plain English — and suggests specific optimizations.
Same MCP connection, different workflows for every team member. Agency CEOs get portfolio health. Media Strategists get campaign QA. Analysts get cross-platform reports. Account Managers get auto-generated QBR decks. Creative Directors get performance-based briefs.
Each role asks in natural language. The MCP server handles the complexity — rate limits, auth, schema normalization, governance — behind the scenes.
SELECT queries with full SQL support, schema introspection (tables, columns, types, indexes), query log analysis, DDL operations (CREATE TABLE, ALTER, materialized views), and INSERT operations. The scope is controlled by the ClickHouse user credentials you provide during setup.
Write operations require explicit user confirmation before execution. You can also scope the ClickHouse credentials to read-only access initially. All executed statements appear in the ClickHouse query log with the MCP session identifier for full auditability.
Yes. Improvado's MCP server connects to any ClickHouse instance accessible over HTTPS or native TCP — whether that's ClickHouse Cloud, a self-managed cluster, or an on-premises deployment. Multi-cluster setups are supported.
The MCP server provides the AI agent with live schema context — table definitions, column types, sample values, and existing indexes. This grounding lets the agent write accurate ClickHouse-dialect SQL, including ARRAY JOIN, window functions, and FINAL modifier usage, without hallucinating column names.
The ClickHouse MCP integration translates natural-language questions into optimized SQL queries that take advantage of ClickHouse's columnar storage and indexing — such as using primary key ranges, partition pruning, and LIMIT clauses — to minimize scan scope. You can also configure query resource limits at the ClickHouse user profile level to cap memory and CPU usage for the integration's dedicated user. For very large tables, it is best practice to ensure queries filter on the primary key or a low-cardinality sort key to keep response times fast.
Yes, pointing the MCP integration to a ClickHouse read replica or a dedicated analytics node is a recommended production pattern. This ensures that AI-driven queries do not compete with your application's write-heavy or latency-sensitive workloads. You simply configure the integration with the host and credentials of the replica, and all queries will be routed there. ClickHouse's native replication keeps replicas close to real-time, so data freshness is typically within seconds.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
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