amineelkouhen/mcp-cockroachdb
by Various
The CockroachDB MCP Server is a natural language interface designed for agentic applications to manage, monitor and query data in CockroachDB.
MCP
amineelkouhen/mcp-cockroachdb
Added 1 June 2026
Overview
The CockroachDB MCP Server provides a natural language interface for agentic applications to manage, monitor, and query data in CockroachDB. It translates natural language requests into database operations using the Model Context Protocol (MCP). This tool is implemented in Python and is open source.
Best for
Best for
Developers building AI agents that need to control and query a CockroachDB database
Use cases
- Execute natural language queries against CockroachDB
- Monitor database health and metrics through agent requests
- Manage database schemas and configurations via conversational commands
Notes
The CockroachDB MCP Server provides a natural language interface for agentic applications to manage, monitor, and query data in CockroachDB. It translates natural language requests into database operations using the Model Context Protocol (MCP). This tool is implemented in Python and is open source.
10 stars on GitHub. Last updated 2026-01-25. Licensed MIT.
Use cases
- Execute natural language queries against CockroachDB
- Monitor database health and metrics through agent requests
- Manage database schemas and configurations via conversational commands
Pros
- Enables AI agents to interact with CockroachDB using natural language
- Open source and written in Python, easy to customize
- Leverages the MCP standard for interoperability with many agent frameworks
Cons
- Small community and limited adoption (10 stars on GitHub)
- May lack robust error handling or advanced query optimization
- Requires the MCP ecosystem and appropriate agent setup
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Enables AI agents to interact with CockroachDB using natural language
- Open source and written in Python, easy to customize
- Leverages the MCP standard for interoperability with many agent frameworks
Cons
- Small community and limited adoption (10 stars on GitHub)
- May lack robust error handling or advanced query optimization
- Requires the MCP ecosystem and appropriate agent setup
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