Timeplus MCP Server

DatabasesPython

Execute SQL queries and manage data in Timeplus

Available Tools

execute_sql

Execute a SQL query against Timeplus and return the results

querytimeout_seconds

list_databases

List all databases in the Timeplus workspace

list_tables

List all tables in a specific database

database

describe_table

Get detailed information about a table's structure

databasetable

generate_sql

Generate SQL for Timeplus based on a natural language description

description

list_kafka_topics

List all available Kafka topics in Timeplus

list_iceberg_tables

List all available Iceberg tables in Timeplus

Timeplus MCP provides a seamless interface for executing SQL queries and managing databases in Timeplus. It allows you to interact with your data, Kafka topics, and Iceberg tables efficiently through natural language. The MCP enhances your data workflows with powerful tools that enable you to query, analyze, and manage your streaming and historical data in Timeplus.

Overview

Timeplus MCP Server provides a powerful interface for interacting with Timeplus databases through natural language. This MCP allows you to execute SQL queries, manage databases, and work with streaming data in Timeplus environments.

Installation

You can install the Timeplus MCP Server using pip:

pip install mcp-timeplus

Alternatively, you can use uv:

uv pip install mcp-timeplus

Configuration

The Timeplus MCP Server requires the following environment variables:

TIMEPLUS_API_KEY: Your Timeplus API key
TIMEPLUS_WORKSPACE: Your Timeplus workspace URL

You can set these environment variables in your shell or in a .env file.

Usage

Once installed, you can add the Timeplus MCP Server to your AI assistant configuration. The MCP provides several tools for interacting with Timeplus:

Use execute_sql to run SQL queries against your Timeplus database
Use list_databases to view available databases
Use list_tables to see tables in a specific database
Use describe_table to get detailed information about a table's structure
Use list_kafka_topics to view available Kafka topics
Use list_iceberg_tables to view available Iceberg tables

When working with the MCP, you can use natural language to describe what you want to do with your data, and the MCP will help translate that into the appropriate SQL queries and commands for Timeplus.

Examples

Here are some examples of how to use the Timeplus MCP:

"Show me all databases in my Timeplus workspace"
"List all tables in the 'analytics' database"
"Describe the structure of the 'users' table"
"Execute a query to find the top 10 users by transaction amount"
"Show me all available Kafka topics"
"List all Iceberg tables in my workspace"

Troubleshooting

If you encounter issues with the Timeplus MCP Server:

Verify that your API key and workspace URL are correctly set
Check that your Timeplus instance is running and accessible
Ensure you have the necessary permissions to access the requested resources
Check the query syntax if you're getting SQL errors

For more information, refer to the Timeplus documentation.