Prometheus MCP. Ask about system health, don't build dashboards.
Prometheus MCP lets you talk to your monitoring system. Instead of building dashboards or running complex PromQL in a terminal, just ask your agent about service health, historical trends, and resource usage. It gives you instant access to time-series data analysis from right inside your chat window.
Give Claude and any AI agent real-world access
Retrieve complex metric expressions over specific time windows using PromQL.
Get instant readings of metrics at a single point in time, like checking if a target is currently up or down.
Discover all available labels for a metric or retrieve metadata to understand what the units and types are.
Perform administrative tasks like creating snapshots of current metrics or cleaning up old, deleted data entries.
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What AI agents can do with Prometheus MCP with 14 Tools
These tools give your agent direct access to every operational function in Prometheus, allowing you to query metrics, analyze trends, and manage data integrity from one place.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Prometheus MCPClean Tombstones
Removes deleted data entries from disk, requiring admin permissions to run.
Delete Series
Deletes specific time series data within a defined range, also requires admin...
Get Label Values
Retrieves every unique value associated with a specified label name.
Get Labels
Lists all available labels attached to the metrics in your environment.
Get Metadata
Pulls detailed metadata about a metric, including its unit and type, scraped from...
Query Range
Evaluates a PromQL expression to show how metrics have changed over an extended period of time.
Query
Runs a PromQL query to get the metric value at one specific moment in time.
Find Series
Locates all time series data that match your specified label selectors.
Create Snapshot
Creates a complete snapshot of all current metric data, requiring admin permissions.
Get Status Buildinfo
Retrieves general build information about the Prometheus instance itself.
Get Status Config
Displays the currently loaded YAML configuration settings for the monitoring stack.
Get Status Flags
Shows all configured flag values set within Prometheus.
Get Status Runtimeinfo
Provides general runtime details and operational information about the monitoring service.
Get Status Tsdb
Retrieves cardinality statistics for the Time Series Database (TSDB).
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Prometheus, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Prometheus. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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The headache of context switching when troubleshooting outages
Today, finding out why service XYZ is slow means opening the monitoring dashboard, running a query to check CPU usage, then opening the logging tool to see errors, and finally opening a separate terminal just to verify network connectivity. You spend more time clicking tabs and copying API endpoints than actually diagnosing.
With this MCP, you stop jumping between apps. Your agent acts as your expert co-pilot. You simply ask it, 'Check latency on service XYZ over the last hour.' It handles all the necessary querying, data fetching, and status checks for you, delivering a single, clear answer right in the chat.
Prometheus MCP: Direct Metric Access
You eliminate the need to manually recall complex PromQL syntax or track which dashboard panel shows which metric. No more hunting through dozens of dropdown menus just to find a specific time series.
The difference is control and speed. You get instant, conversational access to your most critical operational data—whether checking current status with `query` or reviewing historical trends using `query_range`. It's immediate answers, every time.
What Prometheus MCP does for your AI
Running an infrastructure check used to mean jumping between Grafana, the command line, and documentation pages just to answer one simple question. Now, connect your Prometheus instance via this MCP, and treat your monitoring stack like a conversation. You simply ask your agent about performance—whether you need to know the average CPU usage over the last hour or if a specific service is currently failing.
It handles the complex PromQL required for instant queries and historical range data retrieval automatically.
This connection doesn't just display numbers; it translates raw metrics into actionable insights using natural language. If you’re working with other monitoring systems, you'll appreciate this focused approach to observability. By connecting through Vinkius, your agent accesses a dedicated stream of system metrics and configurations, letting you bypass manual dashboard building entirely.
You get the power of an SRE or DevOps engineer talking directly to you.
019e38db-cdb5-720b-9e9b-448800ac7d43 How to set up Prometheus MCP
The bottom line is that your monitoring data becomes available through natural language prompts, eliminating the need for manual dashboard construction.
You subscribe to the MCP and provide your Prometheus server URL and any necessary authentication tokens.
Your AI client recognizes the connection and lets you ask questions about system health or performance metrics in plain English.
The agent translates your request into the correct PromQL query, executes it against the live data, and presents a clear, conversational answer.
Who uses Prometheus MCP
The ops engineer who's tired of clicking through dashboards at 2 am. This MCP is essential for SRE teams and platform developers needing instant metric access without leaving their primary chat or coding environment.
Instantly troubleshoot incidents by running live queries against metrics and checking system configurations without switching tabs.
Verify service performance, check resource consumption patterns, and audit infrastructure health directly from their IDE or terminal chat.
Automate the creation of infrastructure health reports by querying metrics and checking monitoring stack configurations via natural language prompts.
Benefits of connecting Prometheus MCP
Stop context switching. Instead of navigating to a separate dashboard tool just to check latency, you ask your agent in the chat, and it executes the necessary query instantly. You get answers without leaving your workspace.
Understand metrics deeply using get_metadata. If you aren't sure what 'http_requests_total' measures or if it's a counter or gauge, run this tool to get clear documentation on units and types.
Audit system health with status tools. Use the MCP to check the loaded configuration (get_status_config) or review runtime information (get_status_runtimeinfo) without needing SSH access to the server.
Troubleshoot historical issues using query_range. Need to know if CPU usage spiked last Tuesday? Specify a time window and get the full trend data back in plain English.
Administer your monitoring stack safely. If you need to clean up old, unneeded metrics or create a specific snapshot of current data, use tools like clean_tombstones or create_snapshot through simple prompts.
Prometheus MCP use cases
Diagnosing a sudden latency spike
The agent needs to know why requests slowed down. The user asks, 'Show me the average request duration over the last 15 minutes.' The MCP executes query_range, providing a clear trend graph and identifying the exact time period when performance dropped.
Verifying service readiness during deployment
Before deploying code, the developer asks, 'Is the user authentication endpoint currently returning 200 OK?' The MCP runs query to check the current status of that specific metric, confirming system availability immediately.
Investigating resource leak patterns
The team needs to determine if memory usage is slowly creeping up. They ask for a historical trend over three days using query_range, allowing the agent to analyze the data and pinpoint potential memory leaks.
Checking monitoring stack integrity
A platform team member needs to verify if the Prometheus configuration has changed. They use the MCP's status tools (like get_status_config) to pull the YAML settings and confirm compliance with internal standards.
Prometheus MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Treating it like a dashboard.
The user tries to visualize every single metric on one screen, leading to information overload and slow loading times across multiple tabs.
Use the MCP to ask targeted questions. Instead of viewing everything, use get_labels first to understand what data points exist, then follow up with a focused query like query for 'up' status.
Manually writing PromQL.
The user spends 10 minutes looking up the correct syntax for calculating averages or filtering by labels across documentation sites.
Describe your need to your agent in plain English. The MCP translates that natural language request into complex PromQL and executes it using query_range.
Ignoring admin limitations.
A user tries to delete data series but doesn't realize the system requires explicit permission to modify stored metrics.
The MCP handles permissions. If you need to clean up old data, use delete_series, knowing the tool itself validates that administrative access is required.
When to use Prometheus MCP
Use this MCP if your primary bottleneck is translating a complex question about system metrics into executable queries. You should connect here when you need immediate answers—'What happened?' or 'Is it working right now?' The goal is conversational querying. Don't use this if your job requires deep, interactive data manipulation in a visual editor, like adjusting dashboard panels in Grafana. For purely visualization-based analysis, dedicated BI tools are better. If you only need to know what metrics are available without running queries, then simply reviewing the Prometheus web UI is sufficient; this MCP adds the crucial layer of natural language access and status checks like get_status_buildinfo that a basic viewer doesn't provide.
Frequently asked questions about Prometheus MCP
How do I query Prometheus metrics using the Prometheus MCP? +
You ask your agent a question in plain English. The agent interprets your request, builds the necessary PromQL expression, and runs the query for you.
Can I use the Prometheus MCP to check service uptime? +
Yes, you can. You simply ask the agent about the 'up' metric for a specific target or service to see if it is currently reporting a value of 1 (healthy).
What does `get_metadata` do in the Prometheus MCP? +
get_metadata lets you check what a metric actually measures. It tells you things like whether the data is counted, measured, or if it's partitioned by status code.
Is `query_range` different from `query` in this MCP? +
query provides a single point-in-time value. You use query_range when you need to see how the metric changed over an entire period of time, giving you a trend.
Do I need admin rights for all tools in the Prometheus MCP? +
No. Basic querying and metadata retrieval are standard. However, administrative actions like create_snapshot or delete_series require elevated permissions.