# Convex Insights

Query a running Convex app's logs + health in natural language (official MCP)...

- Repository: https://github.com/openclaw/clawhub (9543 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add openclaw/clawhub --skill convex-insights -g -a claude-code -y`
Codex: `npx skills add openclaw/clawhub --skill convex-insights -g -a codex -y`
Cursor: `npx skills add openclaw/clawhub --skill convex-insights -g -a cursor -y`
Gemini CLI: `npx skills add openclaw/clawhub --skill convex-insights -g -a gemini-cli -y`

## Description

Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality, scoped, evidence-backed, with a dashboard deep link.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

<!-- GENERATED from convex-agents content/capabilities/convex-insights.json, do not edit by hand. -->

# Query logs + health in natural language

The deployment already records what happened; the agent just has to ask well. This capability is a disciplined wrapper over the official Convex MCP's read tools (`logs`, `insights`, `functionSpec`, `status`) that turns operational questions into narrow, evidence-returning queries and hands back answers a human can one-click verify in the dashboard. The discipline is copied from the observability MCP surface that works best in the wild: discover fields before querying, three views not fifteen tools, token-frugal output, and a dashboard deep link on every answer.

## Workflow

The rest: https://github.com/openclaw/clawhub/blob/HEAD/.agents/skills/convex-insights/SKILL.md