Hologres MCP Server
by spyfree
Hologres MCP Server serves as a universal interface between AI Agents and Hologres databases. It enables seamless communication between AI Agents and Hologres, helping AI Agents retrieve Hologres database metadata and execute SQL operations.
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What is Hologres MCP Server?
Hologres MCP Server is a universal interface that facilitates communication between AI Agents and Hologres databases, allowing AI Agents to retrieve metadata and execute SQL operations.
How to use Hologres MCP Server?
The server can be installed using either a local repository or PIP. Configuration is done through environment variables. It can be run in SSE mode (default) or STDIO mode, specifying the transport mode via command-line arguments. Examples are provided for Python and Node.js clients.
Key features of Hologres MCP Server
Dual Transport Mode Support (STDIO and SSE)
Database Metadata Access
SQL Execution
Statistics Management
Query Planning
Use cases of Hologres MCP Server
Integrating AI Agents with Hologres databases
Retrieving database schema and table information
Executing SQL queries from AI applications
Collecting and viewing table statistics
Getting query and execution plans
FAQ from Hologres MCP Server
What is the default transport mode?
What is the default transport mode?
The default transport mode is SSE.
How do I configure the server?
How do I configure the server?
The server is configured through environment variables like HOLOGRES_HOST, HOLOGRES_PORT, HOLOGRES_USER, HOLOGRES_PASSWORD, and HOLOGRES_DATABASE.
What are the prerequisites for development?
What are the prerequisites for development?
Python 3.10 or higher and uv for package management are required.
How do I run the server in STDIO mode?
How do I run the server in STDIO mode?
Run the server with the command hologres-mcp-server --transport stdio after setting the necessary environment variables.
What is Model Context Protocol (MCP)?
What is Model Context Protocol (MCP)?
Model Context Protocol (MCP) is an open protocol that standardizes how AI applications communicate with external data sources and tools.