mcp-victoriatraces
Verified Safeby VictoriaMetrics-Community
Overview
Provides a Model Context Protocol (MCP) server for VictoriaTraces, enabling AI clients to query trace data, list services and operations, and search embedded documentation.
Installation
docker run -d --name mcp-victoriatraces -e VT_INSTANCE_ENTRYPOINT=<YOUR_VT_INSTANCE_URL> -e MCP_SERVER_MODE=http -e MCP_LISTEN_ADDR=:8081 -p 8081:8081 ghcr.io/victoriametrics-community/mcp-victoriatracesEnvironment Variables
- VT_INSTANCE_ENTRYPOINT
Security Notes
The server follows good security practices by relying on environment variables for sensitive configuration (like `VT_INSTANCE_BEARER_TOKEN`), which can be managed via Kubernetes secrets. Input validation is present for tool parameters, helping prevent common injection vulnerabilities. The build process includes vulnerability (govulncheck) and license (wwhrd) checks. No explicit `eval` or code obfuscation was found. Network exposures are standard for a server (HTTP/SSE/gRPC) and endpoints like `/metrics` can be protected with auth keys. The security of the backend VictoriaTraces instance is crucial as this server acts as a proxy.
Similar Servers
mcp-victoriametrics
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.
mcpcat-typescript-sdk
This SDK integrates analytics and telemetry capabilities into existing Model Context Protocol (MCP) servers, capturing user intentions, tool usage, and error patterns.
mcp-victorialogs
The Model Context Protocol (MCP) server for VictoriaLogs provides an interface for AI clients to interact with VictoriaLogs APIs and documentation, enabling querying logs, exploring data, viewing instance parameters, and accessing log statistics.
mcpcat-python-sdk
An analytics and observability SDK for Multi-modal Conversational Platform (MCP) servers, capturing user behavior and tool interactions for product development and debugging.