"clickhouse" matching MCP servers:

Enables MCP clients to explore ClickHouse schemas, run analytical queries, and manage the database with statement-aware security modes and access-control flags.

Provides AI agents safe, read-only access to a ClickHouse database, enabling table listing, query execution, schema inspection, and caching.

Enables interaction with ClickHouse databases via MCP, providing tools to list databases and tables and execute safe SELECT, SHOW, and DESCRIBE queries.

Tracks a user's activity by trace ID from application logs stored in ClickHouse. Provides tools for log timeline, trace summaries, and search across services.

Enables AI assistants to query Grafana datasources (Prometheus/Loki metrics and SQL databases like ClickHouse/Postgres/MySQL) and search or inspect dashboards through natural language, using read-only access to Grafana's API.

Ranks log patterns by volume and cost on Splunk, Datadog, Elasticsearch, CloudWatch and ClickHouse, and plans compact, tier down or offload for the excess over each cap. Runs locally over stdio; no log data reaches log10x. Read-only against a public demo dataset without an API key.

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.

A Model Context Protocol server that provides access to Aiven services (PostgreSQL, Kafka, ClickHouse, Valkey, OpenSearch), enabling LLMs to build full stack solutions by interacting with these services.

Enables AI agents to query MySQL, ClickHouse, Trino, and S3-compatible object stores through the same local daemon used by VSCode, including running SQL from files and browsing buckets.

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

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

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.

Enables AI to execute SQL queries against MySQL and ClickHouse connections, retrieve and manage results, and inject them into the aiQueryLab VSCode IDE.