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Query local data sources with an embedded ClickHouse-powered SQL OLAP engine.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "chdb-mcp" yet — see the docs or source repo.
Use chdb-mcp to read sales.parquet, users.csv, and events.json, then summarize monthly revenue, active users, and conversion rate, and output the SQL and result table.
Returns executable SQL and a monthly summary table of key metrics.
I already have a pandas DataFrame named df_orders in Python. Use chdb-mcp to find the top 10 customers by order amount in the last 30 days and provide the query.
Outputs the SQL query for the DataFrame and lists the top 10 customers.
Use chdb-mcp to check data quality in inventory.csv: count nulls, duplicate rows, and abnormal prices, then generate a brief field-level report.
Returns the inspection SQL, quality statistics, and a concise issue report.
Connect to multiple databases to explore schemas and run SQL queries.
Optimize ClickHouse queries, analyze pipeline latency, and monitor data quality safely.
Safely explore and analyze data across multiple databases with read-only access.
Query ClickHouse clusters and list databases or tables via natural language.
Connect to multiple databases to query, inspect schemas, and access remotely via SSH.
Connect to PostgreSQL and MySQL, run SQL, and manage database transactions.