Monitoring & Observability Basic Auth

Prometheus REST API

Pull-based monitoring system with powerful query language

Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. It collects and stores metrics as time series data, providing a powerful query language (PromQL) for analysis and visualization. Developers use Prometheus to monitor infrastructure, applications, and services with dimensional data modeling and built-in alerting.

Base URL http://localhost:9090/api/v1

API Endpoints

Method	Endpoint	Description
GET	`/query`	Evaluates an instant query at a single point in time. Requires a PromQL expression in the query parameter.
GET	`/query_range`	Evaluates an expression query over a range of time. Accepts start, end, and step parameters to define the time window.
GET	`/series`	Returns the list of time series that match a certain label set
GET	`/labels`	Returns a list of label names. Optionally filtered by start and end time parameters.
GET	`/label//values`	Returns a list of label values for a provided label name. The label_name is specified in the path.
GET	`/targets`	Returns an overview of the current state of the Prometheus target discovery
GET	`/rules`	Returns a list of alerting and recording rules. Includes rule groups, evaluation times, and health status.
GET	`/alerts`	Returns a list of all active alerts. Includes alert state, labels, annotations, and firing duration.
GET	`/alertmanagers`	Returns an overview of the current state of the Prometheus alertmanager discovery
GET	`/status/config`	Returns the current Prometheus configuration. Includes the YAML config as loaded at startup.
GET	`/status/flags`	Returns the flag values that Prometheus was configured with. Shows command-line flags and their current values.
GET	`/status/runtimeinfo`	Returns runtime information about the Prometheus server. Includes startup time, storage retention, and Go runtime details.
GET	`/metadata`	Returns metadata about metrics currently scraped from targets
POST	`/admin/tsdb/snapshot`	Creates a snapshot of all current data into a subdirectory. Returns the snapshot directory name for backup purposes.
POST	`/admin/tsdb/delete_series`	Deletes data for a selection of series in a time range. Requires match[] selectors and optional start/end timestamps.

Code Examples

curl -G 'http://localhost:9090/api/v1/query' \
  --data-urlencode 'query=up' \
  --data-urlencode 'time=2024-01-15T10:30:00.000Z' \
  -u 'admin:password'

const queryMetrics = async () => {
  const params = new URLSearchParams({
    query: 'rate(http_requests_total[5m])',
    time: new Date().toISOString()
  });
  
  const response = await fetch(
    `http://localhost:9090/api/v1/query?${params}`,
    {
      headers: {
        'Authorization': 'Basic ' + btoa('admin:password')
      }
    }
  );
  
  const data = await response.json();
  console.log(data.data.result);
};

queryMetrics();

import requests
from requests.auth import HTTPBasicAuth
from datetime import datetime

url = 'http://localhost:9090/api/v1/query'
params = {
    'query': 'up{job="prometheus"}',
    'time': datetime.utcnow().isoformat() + 'Z'
}

response = requests.get(
    url,
    params=params,
    auth=HTTPBasicAuth('admin', 'password')
)

data = response.json()
for result in data['data']['result']:
    print(f"Metric: {result['metric']}, Value: {result['value'][1]}")

Use Prometheus from Claude / Cursor / ChatGPT

Prometheus is a self-hosted protocol — it lives on a host you operate (default http://localhost:9090/api/v1). A hosted MCP gateway can't reach localhost on your machine, so the usual one-click setup doesn't apply. These are the tools an MCP for Prometheus would expose:

query_prometheus_metrics Execute PromQL queries to retrieve current metric values and analyze system health

get_metric_history Query time-series data over a range to analyze trends and patterns in metrics

list_active_alerts Retrieve all currently firing alerts with their labels and annotations

discover_targets Get the current status of all monitored targets and their health state

analyze_metric_cardinality Examine metric labels and cardinality to optimize monitoring performance

Run an Prometheus MCP locally

The local-CLI version of these tools is on the way (npx @meru/rest-mcp --vendor=prometheus · BYO connection string · zero secrets sent to us). For now use the patterns below in your own MCP server, or self-host one from the IOX templates.

Build your own Prometheus MCP →

Prometheus REST API

API Endpoints

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Code Examples

Use Prometheus from Claude / Cursor / ChatGPT

Run an Prometheus MCP locally

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