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  3. Clickhouse Dataops Mcp
C
Health: Not checked yetWe have not completed a health check for this listing yet.Last checked 8/10/2026, 11:45:28 PM

Clickhouse Dataops Mcp

Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
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DataOps ClickHouse MCP server with query optimization and pipeline monitoring

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

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Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Install Config Generator

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claude_desktop_config.json
{
  "mcpServers": {
    "clickhouse-dataops-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "clickhouse-dataops-mcp"
      ]
    }
  }
}

πŸ’‘ Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

Install Directory Badge Claim listing AlternativesπŸ—„οΈ More in Databases

Documentation Overview

clickhouse-dataops-mcp

mcp-name: io.github.Aguantar/clickhouse-dataops-mcp

A DataOps-focused MCP server for ClickHouse with query optimization, pipeline latency analysis, and data quality monitoring.

Features

Unlike generic ClickHouse MCP servers that only run queries, this server acts as a query optimization advisor:

  • ch_query β€” Execute SELECT with automatic partition pruning warnings
  • ch_explain_query β€” EXPLAIN-based analysis with optimization suggestions
  • ch_table_schema β€” Comprehensive table metadata (columns, keys, partitions, samples)
  • ch_pipeline_latency β€” CDC pipeline per-segment latency (p50/p95/p99)
  • ch_data_quality β€” Null/duplicate/gap detection with market coverage checks
  • ch_slow_queries β€” Slow query detection with root cause diagnosis
  • ch_disk_usage β€” Disk analysis with TTL and optimization recommendations
  • ch_list_tables β€” Table catalog with built-in descriptions

Safety

All queries are read-only. DDL/DML operations are blocked at the SQL validation layer:

  • Blocked: DROP, TRUNCATE, DELETE, ALTER, INSERT, UPDATE, CREATE, etc.
  • Multi-statement queries blocked (; separator)
  • Comment-based bypass prevented (comments stripped before validation)
  • System tables restricted to allowlist
  • Query timeout: 30 seconds
  • Row limit enforcement

Installation

Terminal
pip install clickhouse-dataops-mcp

Usage with Claude Code

Add to your .mcp.json:

config.json
{
  "mcpServers": {
    "clickhouse": {
      "command": "clickhouse-mcp-server",
      "env": {
        "CLICKHOUSE_HOST": "localhost",
        "CLICKHOUSE_PORT": "8123",
        "CLICKHOUSE_DATABASE": "cdc_pipeline"
      }
    }
  }
}

Environment Variables

VariableDefaultDescription
CLICKHOUSE_HOSTlocalhostClickHouse HTTP host
CLICKHOUSE_PORT8123ClickHouse HTTP port
CLICKHOUSE_USERdefaultClickHouse username
CLICKHOUSE_PASSWORD(empty)ClickHouse password
CLICKHOUSE_DATABASEcdc_pipelineDefault database
CLICKHOUSE_QUERY_TIMEOUT30Query timeout in seconds

License

MIT

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Frequently Asked Questions about Clickhouse Dataops Mcp

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "clickhouse-dataops-mcp": { "command": "npx", "args": ["-y", "clickhouse-dataops-mcp"] } }

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Technical Specs & Signals

CategoryπŸ—„οΈDatabases
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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