Frequently Asked Questions (FAQ) about VictoriaMetrics MCP Server

Q: What is the VictoriaMetrics MCP Server?

A: The VictoriaMetrics MCP Server is an implementation of the Model Context Protocol (MCP) server that enables seamless integration between VictoriaMetrics and AI models. It allows you to query metrics, explore data, analyze alerting rules, and automate tasks using AI.

Q: What is Model Context Protocol (MCP)?

A: MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). In this case, it allows AI models to access and interact with your VictoriaMetrics data.

Q: What are the key features of the VictoriaMetrics MCP Server?

A: Key features include seamless integration with various MCP clients, enhanced monitoring and observability, a comprehensive toolset for interacting with VictoriaMetrics, embedded documentation, streamlined configuration, and example prompts.

Q: What tools are available in the MCP Server?

A: Available tools include query, query_range, metrics, labels, label_values, series, export, rules, alerts, flags, metric_statistics, active_queries, top_queries, tsdb_status, tenants, documentation, metric_relabel_debug, downsampling_filters_debug, and retention_filters_debug.

Q: What are some use cases for the VictoriaMetrics MCP Server?

A: Use cases include proactive anomaly detection, intelligent alerting, automated troubleshooting, capacity planning, performance optimization, unused metrics identification, rarely used metrics analysis, and documentation search.

Q: What is the relationship between the VictoriaMetrics MCP Server and UBOS?

A: UBOS is a full-stack AI Agent development platform that complements the VictoriaMetrics MCP Server. UBOS provides a centralized platform for orchestrating and managing AI Agents that interact with the MCP Server, enabling complex workflows and integration with enterprise data sources.

Q: How do I install the VictoriaMetrics MCP Server?

A: You can install the MCP Server using Go, Source Code, or Binaries. Docker support is coming soon. Follow the instructions in the Installation section of the documentation.

Q: How do I configure the VictoriaMetrics MCP Server?

A: Configure the MCP Server using environment variables, specifying the URL to your VictoriaMetrics instance, instance type, and authentication token (if required). See the Configuration section for details.

Q: Which MCP clients are supported?

A: Supported MCP clients include Cursor, Claude Desktop, VS Code, Zed, JetBrains IDEs, and Windsurf. Amazon Bedrock support is coming soon.

Q: How do I use the VictoriaMetrics MCP Server with my AI assistant?

A: After installing and configuring the MCP Server, you can start a dialog with your AI assistant by including a phrase like “Use MCP VictoriaMetrics in the following answers.” However, it’s often not required, as the assistant may automatically use the tools if it deems it necessary based on your question.

Q: Can the VictoriaMetrics MCP Server guarantee the accuracy of results?

A: No, AI services and agents along with MCP servers cannot guarantee the accuracy, completeness, and reliability of results. You should always double-check the results obtained with AI. The quality of the MCP Server and its responses depends very much on the capabilities of your client and the quality of the model you are using.