AI Agent for Prometheus MCP
Integrate your Prometheus metrics with Model Context Protocol (MCP) for seamless monitoring and advanced analytics. This AI-powered integration enables automated PromQL queries, instant metric discovery, and direct data analysis, empowering AI assistants to interact with your infrastructure metrics securely and efficiently.
Automate PromQL Query Execution
Empower your AI assistants to execute PromQL queries on demand. Instantly fetch real-time and historical data, analyze trends, and gain actionable insights from your Prometheus setup with standardized MCP interfaces.
- Execute PromQL Queries.
- Run instant or range PromQL queries directly on your Prometheus instance for real-time and historical data insights.
- View Query Results.
- AI agents can retrieve and analyze query results instantly, enabling faster troubleshooting and reporting.
- Discover Metrics.
- List and explore all available metrics to quickly identify trends and anomalies.
- Authentication Support.
- Secure your queries with basic auth or bearer tokens configured by environment variables.
Comprehensive Metric Discovery & Metadata
Quickly list all available Prometheus metrics, fetch metadata for specific metrics, and gain deeper visibility into your monitoring landscape. Streamline metric exploration and enable AI-powered metric analytics.
- List Available Metrics.
- AI assistants can enumerate all metrics in your Prometheus server for better observability.
- Fetch Metric Metadata.
- Retrieve essential metadata for any metric, streamlining documentation and troubleshooting.
- Scrape Target Visibility.
- Get an overview of all scrape targets to monitor infrastructure health and coverage.
Flexible, Secure, and Easy Deployment
Deploy the Prometheus MCP Server securely with Docker container support, environment-based configuration, and robust authentication. Enable multi-tenant support for complex environments and ensure reliable monitoring for every use case.
- Containerized Deployment.
- Quickly deploy with Docker for portability and scalability.
- Multi-Tenant Support.
- Use environment variables to enable support for multi-tenant Prometheus setups like Cortex, Mimir, or Thanos.
- Configurable Tool Access.
- Select which MCP tools are available to clients, optimizing security and performance.
MCP INTEGRATION
Available Prometheus MCP Integration Tools
The following tools are available as part of the Prometheus MCP integration:
- execute_query
Execute a PromQL instant query against Prometheus to retrieve real-time metric data.
- execute_range_query
Run a PromQL range query over a specified time window with customizable step intervals.
- list_metrics
List all available metrics in the connected Prometheus instance for exploration and integration.
- get_metric_metadata
Get detailed metadata for a specific metric, including help text and type information.
- get_targets
Retrieve information about all active and inactive Prometheus scrape targets.
Unlock AI-Powered Prometheus Insights
Connect Prometheus to your AI assistants and run PromQL queries with ease. Explore metrics, automate analysis, and streamline observability with the Prometheus MCP Server.
What is Prometheus MCP Server
Prometheus MCP Server is an open-source Model Context Protocol (MCP) server that enables AI assistants to query and analyze metrics from Prometheus through standardized interfaces. Developed and maintained on GitHub, this server acts as a bridge between Prometheus—a leading system monitoring and alerting toolkit—and AI systems by allowing them to execute PromQL queries, discover available metrics, retrieve metadata, and analyze time-series data in real time. The server supports secure authentication via basic auth or bearer tokens, is containerized for easy deployment with Docker, and is designed to make real-time system monitoring and performance insights accessible to AI-powered workflows and automation tools. Its flexible design allows users to configure which tools and functionalities are exposed to the MCP client, optimizing the context window and resource utilization.
Capabilities
What we can do with Prometheus MCP Server
Prometheus MCP Server enables seamless interaction between AI assistants and Prometheus monitoring infrastructure. It allows users to execute complex metrics queries, automate system health checks, and retrieve detailed metadata for operational analytics—all through a standardized protocol interface.
- Execute PromQL queries
- Run instant and range queries against Prometheus to monitor real-time or historical metrics.
- Discover and explore metrics
- List all available metrics, inspect metadata, and understand data structure for advanced monitoring.
- Secure authentication
- Integrate with Prometheus instances using basic auth or bearer tokens for secure access.
- Docker containerization
- Deploy the MCP server quickly and reliably using Docker, ensuring consistent environments.
- Interactive AI tools
- Provide AI systems with configurable, interactive monitoring and analysis capabilities.
What is Prometheus MCP Server
AI agents can leverage Prometheus MCP Server to gain powerful, real-time insights into system performance and health. By integrating with Prometheus, AI agents can automate monitoring, detect anomalies, optimize resource allocation, and trigger alerts or remediation actions, all using standardized query interfaces. This enables truly autonomous, intelligent operations and system management.