mcp-victoriametrics
Verified Safeby VictoriaMetrics-Community
Overview
Acts as a Model Context Protocol (MCP) server for VictoriaMetrics, enabling AI integration for monitoring, observability, and debugging tasks through its APIs and embedded documentation.
Installation
docker run -d --name mcp-victoriametrics -e VM_INSTANCE_ENTRYPOINT=https://play.victoriametrics.com -e VM_INSTANCE_TYPE=cluster -e MCP_SERVER_MODE=sse -e MCP_LISTEN_ADDR=:8080 -p 8080:8080 ghcr.io/victoriametrics-community/mcp-victoriametricsEnvironment Variables
- VM_INSTANCE_ENTRYPOINT
- VM_INSTANCE_TYPE
- VM_INSTANCE_BEARER_TOKEN
- VM_INSTANCE_HEADERS
- VM_DEFAULT_TENANT_ID
- VMC_API_KEY
- MCP_SERVER_MODE
- MCP_LISTEN_ADDR
- MCP_DISABLED_TOOLS
- MCP_DISABLE_RESOURCES
- MCP_HEARTBEAT_INTERVAL
- MCP_LOG_FORMAT
- MCP_LOG_LEVEL
Security Notes
The server uses environment variables for sensitive credentials like API keys and bearer tokens, which is a good practice. It processes user input for queries, relabeling, and rule testing, but the Go implementation appears to use trusted internal libraries (e.g., `metricsql.Prettify`, `vmalert-tool/unittest`) and standard HTTP client practices with URL encoding, reducing the risk of direct command injection or arbitrary code execution. Temporary files are created for rule testing, which is handled via `os.MkdirTemp` and `os.WriteFile`, followed by an internal library call, minimizing external command execution risks. No obvious obfuscation or highly dangerous patterns like `eval` in the Go runtime were found.
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