chaitin/monkeycode

AI coding platform for teams

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Summary Information

Updated 2 minutes ago
Added to GitGenius on September 14th, 2026
Created on June 25th, 2025
Open Issues & Pull Requests: 338 (-1)
GitHub issues: Enabled
Number of forks: 716
Total Stargazers: 4,700 (+0)
Total Subscribers: 33 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 5.1 days
Mean response time: 46.1 days
90th percentile: 180.2 days
Tracked items: 272

Most active contributors

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How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Almost all tracked open issues have seen activity in the last three months. Only 7% of issues opened in the past year have been closed. Three people close 92% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 316
New in 7 days: 12
Closed in 7 days: 1
Avg open age: 47 days
Stale 30+ days: 215
Stale 90+ days: 17

Recent activity

Opened in 7 days: 10
Closed in 7 days: 1
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • to be verified (3)
  • bug (1)
  • ready-for-agent (1)

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Detailed Description

MonkeyCode is an enterprise-grade AI development platform that provides integrated management of development environments, AI models, tasks, and project requirements for teams.

The platform addresses the fragmentation that occurs when teams try to assemble multiple AI coding tools and environments. Rather than requiring developers to jump between separate applications, MonkeyCode consolidates the workflow into a single system where AI agents can work from requirement specification through development to validation. The tool distinguishes itself from typical AI coding assistants by targeting professional engineering teams rather than individual developers, with centralized workflow management that allows engineering leaders to oversee AI-assisted development at scale.

Teams should consider MonkeyCode if they need to deploy AI coding capabilities across an organization while maintaining control over models, environments, and task execution. The platform supports both self-hosted deployment within enterprise networks and a managed online environment with built-in language models and native mobile support. This dual deployment model makes it suitable for organizations with varying infrastructure requirements, from those needing air-gapped solutions to those preferring managed services. The tool is written in TypeScript and includes both a web interface and an Electron-based client.

The project maintains active continuous integration workflows for both service builds and client releases. Development activity shows ongoing work across multiple deployment targets and regular updates to the codebase.