# SigNoz

> Use this tool when you need to integrate SigNoz observability data into AI-powered workflows for performance analysis and troubleshooting. It provides comprehensive access to SigNoz data through HTTP and STDIO transport modes, supporting custom metrics querying, dashboard management, and standardized APM metrics collection. Ideal for DevOps teams, SREs, and organizations seeking automated observability analysis and incident investigation.

Canonical page: https://skillsregistry.net/skills/drdroidlab-signoz  
JSON: https://api.skillsregistry.net/v1/skills/drdroidlab-signoz

## Description

This MCP server provides AI assistants with comprehensive access to SigNoz observability data through a Flask-based implementation built by Doctor Droid that supports both HTTP and STDIO transport modes. The implementation offers six core tools including connection testing, dashboard management (listing and fetching detailed panel data), custom metrics querying with PromQL support, and standardized APM metrics collection (request rate, error rate, latency) with hardcoded builder query templates that match SigNoz's frontend behavior. Built with Docker containerization, configurable SSL verification, and intelligent timestamp handling that defaults to 3-hour lookbacks, it serves DevOps teams needing AI-powered observability analysis, SREs requiring automated dashboard data extraction and incident investigation, and organizations wanting to integrate SigNoz monitoring data into conversational workflows for performance analysis and troubleshooting.

## Trust

- **Trust score (0–1):** 0.78
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/drdroidlab-signoz)
- **Repository:** <https://github.com/drdroidlab/signoz-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "drdroidlab-signoz"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/drdroidlab-signoz` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/drdroidlab-signoz/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt