triggerdotdev/trigger.dev

Trigger.dev – build and deploy fully‑managed AI agents and workflows

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Summary Information

Updated 26 minutes ago
Added to GitGenius on September 3rd, 2026
Created on November 30th, 2022
Open Issues & Pull Requests: 352 (+1)
GitHub issues: Enabled
Number of forks: 1,441
Total Stargazers: 16,225 (+0)
Total Subscribers: 56 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2.5 days
Mean response time: 84.7 days
90th percentile: 388.4 days
Tracked items: 553

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 82% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "area/docs" is answered fastest, typically in about 11 hours, while "bug" waits about 4 weeks. 58% of tracked open issues have had no activity in three months. Only 8% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 267
New in 7 days: 9
Closed in 7 days: 2
Avg open age: 202 days
Stale 30+ days: 228
Stale 90+ days: 168

Recent activity

Opened in 7 days: 6
Closed in 7 days: 1
Comments in 7 days: 0
Events in 7 days: 4

Top labels

  • area/integrations (36)
  • enhancement (33)
  • bug (21)
  • area/server (18)
  • area/docs (12)
  • documentation (9)
  • 💰 Rewarded (7)
  • v3 (6)

Detailed Description

Trigger.dev is a workflow orchestration platform that enables developers to build and deploy AI agents and automated workflows with managed execution and scheduling.

The platform addresses the challenge of running complex, long-running tasks and AI agent logic reliably in production. It provides a TypeScript-based framework where developers define workflows and agents as code, then deploy them to Trigger.dev's managed infrastructure for execution. The service handles scheduling, retries, error handling, and state management, allowing developers to focus on business logic rather than infrastructure concerns. The platform integrates with Next.js and supports background job execution, making it suitable for applications that need to orchestrate tasks asynchronously or run AI agents that interact with external systems.

Trigger.dev is well-suited for teams building AI-powered applications, automation platforms, or systems requiring reliable task orchestration. It works particularly well for projects where you need scheduled execution, long-running workflows, or agent-based automation without managing your own job queue infrastructure. The platform's support for Model Context Protocol servers positions it as a natural choice for applications that need to connect AI agents to multiple external tools and data sources.

Development activity shows consistent engagement with the codebase through regular commits and active issue management. The project maintains an organized approach to feature development and bug fixes, with clear communication through its changelog. The team demonstrates responsiveness to the community through pull request reviews and issue triage, indicating ongoing investment in the platform's stability and feature set.