| name | query-datasource |
| description | Query data from various datasources in a Nightingale (n9e) environment. Supports Prometheus metric queries, Elasticsearch/Loki log queries, and SQL datasource queries such as ClickHouse/MySQL/PostgreSQL/TDengine/Doris. Use when the user asks to query metrics, view monitoring data, search logs, or run PromQL or SQL queries. |
| tags | ["internal"] |
Nightingale (n9e) Query Datasource Data
Query monitoring metrics, logs, and time-series data from various datasources on the Nightingale monitoring platform.
Based on the datasource type the user needs, read the corresponding file under the datasources/ directory to get the query method and parameter format:
Prerequisites
The user needs to provide:
- n9e address: e.g.
http://<n9e-host>:<port>
- Username/password: e.g.
<username>/<password>
- Query requirement description: e.g. "query CPU usage over the last hour", "search logs containing error"
If the user has not provided the above information, use the AskUserQuestion tool to ask.
Execution Steps
Step 1: Log in to obtain a Token
POST /api/n9e/auth/login
Content-Type: application/json
Body: {"username":"<username>","password":"<password>"}
Extract dat.access_token from the response, and include Authorization: Bearer <token> in all subsequent requests.
Step 2: Query available datasources
Retrieve the datasource list to determine the datasource ID and type to query:
POST /api/n9e/datasource/list
Authorization: Bearer <token>
Content-Type: application/json
Body: {}
Each datasource in the response contains id, name, and plugin_type.
If the user has not specified a datasource, use the AskUserQuestion tool to display the available datasources and let the user choose.
Step 3: Run the query based on the datasource type
Based on the datasource's plugin_type, read the corresponding datasources/*.md file to get the query API and parameter format.
Step 4: Format the output
Present the query result to the user as a readable Markdown table or list.
Datasource Type Quick Reference
Generic Proxy API
All datasources can access their native APIs through the generic proxy:
<ANY_METHOD> /api/n9e/proxy/<datasource_id>/<native API path>
Authorization: Bearer <token>
For example:
- Prometheus:
/api/n9e/proxy/1/api/v1/query?query=up
- Elasticsearch:
/api/n9e/proxy/2/_cat/health
- Loki:
/api/n9e/proxy/3/loki/api/v1/labels
Generic Time-Series Query API
All datasources (except Prometheus) can use the unified time-series query endpoint:
POST /api/n9e/ds-query
Authorization: Bearer <token>
Content-Type: application/json
{
"cate": "<plugin_type>",
"datasource_id": 1,
"query": [<query object>]
}
Generic log query endpoint:
POST /api/n9e/logs-query
Authorization: Bearer <token>
Content-Type: application/json
{
"cate": "<plugin_type>",
"datasource_id": 1,
"query": [<query object>]
}
The exact structure of the query object varies by datasource type; see each datasource file for details.
Generic Metadata API for SQL-type Datasources
ClickHouse, MySQL, PostgreSQL, and Doris share the following metadata query endpoints:
POST /api/n9e/db-databases // List databases
POST /api/n9e/db-tables // List tables
POST /api/n9e/db-desc-table // View table structure
TDengine uses dedicated endpoints:
POST /api/n9e/tdengine-databases
POST /api/n9e/tdengine-tables
POST /api/n9e/tdengine-columns
Key Considerations
- Query the datasource list first to get the ID: All queries require a
datasource_id; obtain it first via POST /api/n9e/datasource/list
- SQL queries are read-only: SQL-type datasources prohibit write operations such as CREATE, INSERT, UPDATE, DELETE, ALTER, DROP
- Time variables: In SQL queries, use
$from and $to to represent the time range; the system replaces them automatically
- keys field: Time-series queries must specify
valueKey (numeric column) and labelKey (grouping column); separate multiple columns with spaces
- Unified response format: All API responses are wrapped in a
{"dat": <data>} structure
