tdengine mcp
A Model Context Protocol (MCP) server that provides read-only TDengine database queries for AI assistants, allowing users to execute queries, explore database structures, and investigate data directly from AI-powered tools.
A Model Context Protocol (MCP) server that provides read-only TDengine database queries for AI assistants, allowing users to execute queries, explore database structures, and investigate data directly from AI-powered tools.
A Model Context Protocol (MCP) server that provides read-only TDengine database queries for AI assistants. Execute queries, explore database structures, and investigate your data directly from your AI-powered tools.
This MCP server works with any tool that supports the Model Context Protocol, including:
.cursor/mcp.json
This tool is designed specifically for data investigation and exploration through read-only queries. It is not intended for database administration, schema management, or data modification.
The recommended way to use this MCP server is to run it directly with uv
without installation. This is how both Claude Desktop and Cursor are configured to use it in the examples below.
If you want to clone the repository:
git clone https://github.com/Abeautifulsnow/tdengine-mcp.git
cd tdengine-mcp
Then you can run the server directly:
uv run src/tdengine_mcp_server -th 192.100.8.22 -db log -ll debug
Alternatively you can change the .env
file in the src/tdengine_mcp_server/
directory to set the environment variables and run the server with the following command:
uv run src/tdengine_mcp_server
Important: the .env file will have higher priority than the command line arguments.
pip
command# Install globally with pip
pip install tdengine_mcp_server
and then run:
python -m tdengine_mcp_server -h
to get the how-to-use infomation.
Environment Variable | Description | Default |
---|---|---|
LOG_LEVEL | Set the log level (DEBUG, INFO, WARN, ERROR) | INFO |
TDENGINE_HOST | Database host for environment | localhost |
TDENGINE_PORT | Database port | 6041 |
TDENGINE_USERNAME | Database username | root |
TDENGINE_PASSWORD | Database password | taosdata |
TDENGINE_DATABASE | Database name | log |
TDENGINE_TIMEOUT | Set the connection timeout in seconds | 30 |
$ python3 -m tdengine_mcp_server -h
usage: __main__.py [-h] [-th TAOS_HOST] [-tp TAOS_PORT] [-tu TAOS_USERNAME] [-pwd TAOS_PASSWORD] [-db TAOS_DATABASE] [-to TAOS_TIMEOUT] [-ll LOG_LEVEL]
TDengine MCP Server
options:
-h, --help show this help message and exit
-th, --taos-host TAOS_HOST
TDengine host address. Default: `localhost`
-tp, --taos-port TAOS_PORT
TDengine port number. Default: `6041`
-tu, --taos-username TAOS_USERNAME
TDengine username. Default: `root`
-pwd, --taos-password TAOS_PASSWORD
TDengine password. Default: `taosdata`
-db, --taos-database TAOS_DATABASE
TDengine database name. Default: `default`
-to, --taos-timeout TAOS_TIMEOUT
TDengine connection timeout. Default: `30`
-ll, --log-level LOG_LEVEL
Log level. Default: `INFO`
Your AI assistant can interact with TDengine databases through the MCP server. Here are some examples:
Example queries:
Can you use the query tool to show me the first 10 records from the database?
I need to analyze our sales data. Can you run a SQL query to get the total sales per region for last month from the development database?
Can you list all the available databases we have?
The TDengine Query MCP server provides three main tools that your AI assistant can use:
Execute read-only SQL queries against a specific stable:
Use the query tool to run:
SELECT * FROM customers WHERE itemid > '2025-01-01' LIMIT 10;
Get detailed information about your stable:
Use the info tool to check the meta info about the specified stable.
DESCRIBE disks_info;
If you're having trouble connecting:
LOG_LEVEL
in your configurationError: Query execution failed
Contributions are welcome! Please feel free to submit a Pull Request.
For more information or support, please open an issue on the GitHub repository.