Description
Raindrop is a monitoring and observability platform for AI agents. Much like error trackers for web apps, it discovers silent agent failures in production that traditional testing misses. Raindrop captures every production run, including messages, tool calls, retries, and errors, in one place, then reads the traces and surfaces the real failures, from hallucinations and loops to broken tools.
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The platform is built around a single workflow: log every agent run, have issues surfaced automatically, investigate them, and prove the fix worked. Detected issues are sent to Slack, where Raindrop acts like a teammate you can @mention to ask questions, triage issues, and create signals. Custom classifiers called Signals let teams define and track any behavior that matters, such as user frustration, task failures, or aesthetic complaints, and watch its rate over time.
Raindrop includes a Triage Agent that investigates issues from Slack, the web, or a coding assistant via MCP, and an Experiments feature that validates fixes against live traffic behind a feature flag before rolling them out. Its MCP integration connects editors like Claude Code, Cursor, and Codex so a local agent can pull full traces and propose patches in your repo. An open-source local development tool, workshop, lets developers inspect traces, replay runs, and debug from localhost.
Built for teams from local testing to enterprise, Raindrop offers SDKs for TypeScript and Python, an HTTP API, SOC 2 Type II compliance, server-side PII redaction, SSO, and a self-hosting beta. Pricing starts with a free Hobby tier and scales through usage-based Pro and Enterprise plans.
- CategoryMLOps & Model Deployment
- Pricing ModelFreemium
- DeploymentCloud, Self-hosted
- PlatformsWeb
Raindrop's Core Features
Full trace capture of every agent run, including tool calls, retries, and errors
Automatic detection of silent failures like hallucinations, loops, and broken tools
Slack integration with @mention triage and alerts
Custom Signals to define and track any agent behavior at scale
Triage Agent that investigates issues from Slack, web, or MCP
Experiments to validate fixes against live traffic behind a feature flag
MCP integration with coding assistants for trace pulls and auto-fix loops
SOC 2 Type II compliance, PII redaction, SSO, and self-hosting beta
How to use Raindrop?
Log every agent run: Instrument your agent with the SDK or HTTP API so Raindrop captures messages, tool calls, retries, and errors.
Surface silent issues: Raindrop reads the traces and sends the real failures to Slack, from hallucinations to broken tools.
Triage in Slack: @mention Raindrop like a teammate to ask questions, investigate issues, and create signals.
Prove the fix: Ship a fix, run an experiment against live traffic behind a feature flag, and confirm the regression is gone.
Raindrop's Use Cases
- Production agent monitoring
- Trace debugging
- Behavior tracking
- Fix validation
- In-editor investigation
