"clickhouse" matching MCP servers:

Read-only MCP server for large-scale cross-sectional quant analysis of US stock market data (1.49 billion rows) using ClickHouse.

Enables executing SQL queries, listing databases, and listing tables on a ClickHouse cluster through natural language.

mcp-clickhouse-long-running

Exposes an Apache Ossie semantic model over MCP so AI agents can discover metrics, dimensions and relationships, then translate business-term questions into a single ClickHouse query. Also serves the generated SQL and model descriptions, letting agents validate and recover from mistakes without knowing ClickHouse specifics.

This read-only MCP server lets AI assistants inspect Apache NiFi, ClickHouse, and Kafka across multiple environments through natural language. It provides health checks, flow and message searches, querying and metadata tools while enforcing OIDC or proxy authentication, per-user auditing, secret masking, and two-lock read-only safeguards.

Enables LLM clients to query ClickHouse analytics tables read-only through MCP, with an allowlist of permitted tables and an optional HTTP healthcheck.

Enables AI agents to discover and query data federated across MySQL/MariaDB, PostgreSQL, ClickHouse, S3 and Kafka with SQL, exposing tools to list databases, schemas, tables and connections, describe columns, search objects, inspect table statistics, run EXPLAIN, and execute arbitrary statements. It runs locally over stdio against a PostgreSQL-wire endpoint and returns structured results or SQLSTATE-coded errors.

Provides access to Aiven's PostgreSQL, Kafka, ClickHouse, Valkey and OpenSearch services, enabling LLMs to build full stack solutions by interacting with the Aiven ecosystem.

Read-only MCP server for FP&A & management reporting — governed metrics, financial statements and drill-down over a SQL semantic layer. Your own financials on your own warehouse, not market data. Open core of Précis. (metric engine · ClickHouse · OIDC · Docker)

MCP server for the OrionBelt Semantic Layer. Enables LLMs to explore governed semantic models, compile YAML metric definitions into optimized SQL across 8 engines (BigQuery, ClickHouse, Databricks, Dremio, DuckDB, MySQL, PostgreSQL, Snowflake), and execute analytics queries via natural language. Works with Claude, Cursor, Windsurf, and Copilot.

Enables an agent to guide secure onboarding, provision required Cloud.ru resources through APIs, stage and import sales CSV data into ClickHouse, and publish and verify revenue and contribution-margin dashboards in Managed BI with cost approval.

Enables AI agents to interact with ClickHouse analytics through a semantic layer, exposing datasets and metrics for natural-language querying.

Turns existing backend APIs (OpenAPI) and SQL databases (PostgreSQL, MariaDB, ClickHouse) into hosted MCP servers for AI clients, with built-in dashboards, forms, and credential encryption.

Syncs Google Search Console performance data into a local ClickHouse database and exposes prepared SEO analysis tools to AI agents. Enables diagnosing traffic drops, finding striking-distance keywords, detecting cannibalization, auditing indexing, and generating weekly SEO reports through natural language.

MCP server for executing SQL queries on PostgreSQL and ClickHouse with per-connection allow/deny policies by statement group.