The IoTDB MCP Server provides a secure interface for AI assistants to interact with Apache IoTDB time-series databases. Developed by the Apache Software Foundation, this Python-based implementation enables three core database operations: executing SELECT queries, listing available tables, and describing table schemas. The server connects to IoTDB instances using a session pool for efficient connection management and returns query results in a structured text format. It's particularly valuable for data analysts and IoT applications that need AI-assisted exploration and analysis of time-series data stored in IoTDB without requiring direct database access.
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Highlight AIExecute SHOW/COUNT queries to read metadata from the database. Input: query_sql (string): The SHOW/COUNT SQL query to execute.
Execute SELECT queries to read data from the database. Input: query_sql (string): The SELECT SQL query to execute using TREE dialect.
Execute a query and export the results to a CSV or Excel file. Input: query_sql (string): The SQL query to execute, format (string): Export format, either 'csv' or 'excel', filename (string): Optional filename for the exported file.
Execute SELECT queries to read data from the database. Input: query_sql (string): The SELECT SQL query to execute using TABLE dialect.
Get a list of all tables in the database. No input required.
View schema information for a specific table. Input: table_name (string): Name of the table to describe.
Execute a query and export the results to a CSV or Excel file. Input: query_sql (string): The SQL query to execute, format (string): Export format, either 'csv' or 'excel', filename (string): Optional filename for the exported file.
