StarRocks MCP

Name: StarRocks MCP
Author: StarRocks

by StarRocks

Sub-second analytics on fresh data with high concurrency via MCP

database Python Intermediate Self-hostable

⭐ 100 stars 📅 Updated: 1mo ago

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Description

MCP server for interacting with StarRocks, an analytics platform designed for sub-second queries on fresh data with high concurrency and low latency. StarRocks excels at real-time dashboards, ad-hoc queries, and data lake analytics. This server lets AI assistants execute SQL queries, explore database schemas, and analyze query performance directly on StarRocks clusters. Compatible with MySQL protocol and supports querying external data sources like Apache Hive, Apache Iceberg, and Delta Lake without data movement. Ideal for teams that need blazing-fast analytics on both internal tables and data lake formats.

✅ Best for

Teams building real-time dashboards and analytics that need sub-second query performance across both internal and lake data

⏭️ Skip if

You need a general-purpose transactional database or only work with small datasets

💡 Use cases

Running sub-second analytical queries from AI assistants for real-time dashboards
Exploring and querying data across internal tables and external data lakes
Analyzing query performance and identifying optimization opportunities
Ad-hoc data exploration with natural language on StarRocks clusters

👍 Pros

✓ Sub-second query latency even on complex analytical workloads
✓ MySQL-compatible protocol — LLMs can generate standard SQL directly
✓ Native data lake analytics (Hive, Iceberg, Delta Lake) without data movement
✓ High concurrency support for dashboard and multi-user scenarios

👎 Cons

✗ Requires a running StarRocks cluster (not trivial to set up locally)
✗ Focused on analytical workloads — not designed for heavy OLTP transactions
✗ Smaller community compared to more established data warehouses

🔧 Exposed tools (4 tools)

Tool	Category	Description
list_databases	discovery	List all available databases and external catalogs
describe_table	discovery	Get schema details and column types for a table
analyze_performance	optimization	Analyze query performance and suggest optimizations
execute_query	query	Execute a SQL query on the StarRocks cluster

⚡ Installation

Prerequisites:

• python v3.10+
• StarRocks database credentials (host, port, user, password)
• API key required

Check Claude Code documentation to configure this MCP server.

💡 Tips & tricks

StarRocks is MySQL-compatible, so use standard SQL syntax. Use describe_table to inspect schemas before writing queries. For data lake analytics, check available external catalogs first. The analyze_performance tool helps identify slow queries and missing indexes.

🔄 Alternatives

Apache Doris MCP

MPP-based real-time data warehouse with analytical SQL via MCP

Similar functionality

bigquery-mcp

MCP server — editorial content pending