AI Agent for VictoriaMetrics MCP
Seamlessly integrate your VictoriaMetrics instance with the Model Context Protocol (MCP) server. Gain powerful monitoring, observability, and automation capabilities using VictoriaMetrics APIs. Effortlessly query, analyze, and debug your metrics data with advanced tools and up-to-date embedded documentation, empowering engineers to optimize operations and ensure reliability.
Unified Metrics Monitoring & API Access
Leverage nearly all read-only VictoriaMetrics APIs for robust querying, visualization, and data exploration. Access metrics, labels, series, and documentation directly via the MCP server to accelerate observability and troubleshooting, whether you're running single-node or cluster instances or using VictoriaMetrics Cloud.
- Comprehensive Metrics Querying.
- Explore and analyze metrics, draw graphs, and visualize trends directly from your VictoriaMetrics instance.
- Cloud & On-Prem Integration.
- Supports both VictoriaMetrics Cloud and self-managed environments for maximum flexibility.
- Embedded Documentation Search.
- Access and search the latest VictoriaMetrics documentation even without online connectivity.
- Seamless API Connectivity.
- Utilize robust endpoints for querying, exporting, and debugging—enabling fast, informed decisions.
Advanced Observability & Automation
Quickly analyze and test alerting rules, explore cardinality, trace queries, and debug configurations. The MCP server empowers you to automate operational tasks, improve incident response, and maintain high system reliability.
- Alert Rule Analysis.
- Test and optimize alerting and recording rules to ensure robust monitoring coverage.
- Cardinality & Usage Stats.
- Explore metric cardinality and usage to optimize storage and query performance.
- Query & Config Debugging.
- Trace, prettify, and debug queries, relabeling, and retention configurations for reliable infrastructure.
Flexible Deployment & Configuration
Deploy the MCP server quickly using Docker, binaries, Go, or Smithery. Configure for your single-node, cluster, or cloud environment with simple environment variables. Multiple operation modes (stdio, SSE, HTTP) support integration with popular AI clients and development tools.
- Multi-Mode Operation.
- Choose from stdio, SSE, or HTTP streaming to match your client’s needs and scale efficiently.
- Easy Setup & Management.
- Install using Docker, Go, binaries, or Smithery CLI for a frictionless onboarding process.
- Secure API Key & Token Support.
- Flexible authentication for both on-prem and cloud deployments using environment variables.
MCP INTEGRATION
Available VictoriaMetrics MCP Integration Tools
The following tools are available as part of the VictoriaMetrics MCP integration:
- query_metrics
Query and explore VictoriaMetrics time series data using flexible search and filtering capabilities.
- list_metrics
List all available metric names in your VictoriaMetrics instance for further analysis.
- list_labels
Retrieve all label names used in your time series data to assist with metric discovery.
- list_label_values
View possible values for any given label key to understand data dimensions and cardinality.
- get_series
Fetch complete time series data for specific metrics or label combinations.
- analyze_cardinality
Analyze and report on series cardinality to optimize metric storage and performance.
- show_instance_info
Display configuration parameters and status information for the connected VictoriaMetrics instance.
- search_docs
Search embedded VictoriaMetrics documentation for relevant topics, guides, and API details.
- test_rules
Test and analyze alerting or recording rules for correctness and expected behavior.
Get Started with VictoriaMetrics MCP Server
Experience seamless monitoring and advanced automation for your VictoriaMetrics instances. Book a demo to see it in action or try FlowHunt free to explore its capabilities yourself.
What is VictoriaMetrics
VictoriaMetrics is a global company specializing in high-performance, scalable, and cost-efficient monitoring and observability solutions. The company is renowned for its open-source time series database designed to efficiently store, process, and query massive amounts of metrics and logs data. VictoriaMetrics provides both open-source and enterprise solutions, supporting on-premise and cloud deployments. Their technology is trusted by businesses around the world to ensure reliable monitoring, streamlined operations, and actionable insights from infrastructure and application data.
Capabilities
What we can do with VictoriaMetrics
VictoriaMetrics enables users and organizations to achieve advanced monitoring, observability, and analytics for their infrastructure and applications. Its solutions are ideal for collecting, storing, and querying time series data efficiently, whether you need a lightweight open-source solution or enterprise-grade features. The platform's flexibility supports both cloud-native and on-prem environments.
- High-performance metrics storage
- Store and retrieve massive volumes of time series data with low resource consumption.
- Scalable observability
- Seamlessly scale monitoring infrastructure without worrying about data loss or performance bottlenecks.
- Real-time analytics
- Run complex queries on metrics and logs data for instant insights and troubleshooting.
- Flexible deployment
- Deploy on-premises, in the cloud, or in hybrid environments based on your organizational needs.
- Open-source and enterprise support
- Choose from free, community-supported solutions or unlock advanced features with the enterprise edition.
How AI Agents Benefit from VictoriaMetrics
AI agents can leverage VictoriaMetrics to monitor system health, gather real-time metrics, and analyze trends for predictive maintenance or automated remediation. With its robust API and scalable architecture, VictoriaMetrics empowers AI systems to access accurate and up-to-date observability data, enabling smarter automation and more reliable operations.