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Source control for agents. Use multiple coding agents, track they change, and query them in one place
This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.
100
review score
Problem solved
Atlas solves the problem of agents starting from zero each session and losing context when switching between different coding agents. It also addresses the lack of visibility into agent actions by recording and making queryable all changes, decisions, and history, which is not provided by existing agent tools.
Deployment reality
The available setup signal starts with: Download from https://github.com/pacifio/atlas/releases. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.
Commercial use
The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.
Capability ceiling
Developers can build complex multi-agent workflows where multiple coding agents collaborate on the same codebase with shared memory and context. They can track every change, query past sessions, and integrate agent knowledge into prompts. The ceiling includes running parallel agent sessions, maintaining a persistent knowledge base, and enabling seamless agent switching without loss of context, suitable for large-scale software projects.
Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.
pacifio/atlas is tracked as a TypeScript project in the AI Agent, MCP Server, AI App, Developer Tool area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.
Momentum check: the repository has 1.0k total stars, with +123 today, +0 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.
Maintenance check: current activity is Active; the latest push was 8 days ago, and the open issue queue is 24, about 2.31% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.
Adoption check: 177 forks and 1.0k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.
Practical fit: this project is most relevant when you need AI prototypes, LLM workflows, and agent-style applications. Be cautious when you need a legal review, security audit, or production SLA.
Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 123. Follow the original GitHub repository for final install, security, and release information.
Analysis
ReadyOriginal problem, capability, and verdict guidance are available.
Sources
ReadyRepository metadata and README/source references are attached.
License
ReadyMIT is recorded for review.
Maintenance
ReadyRecent activity is visible in repository metadata.
Alternatives
ReadyEnough nearby projects exist for comparison.
Momentum
1.0k Stars
Reuse
177 Forks
Attention
1.0k Watchers
Maintenance
active
License
MIT
Open issues
24
Atlas is an open-source source control tool for coding agents, enabling parallel execution of multiple agents like Claude Code and Codex while tracking their changes, sessions, and decisions. It provides shared memory and context across agents, ensuring continuity and queryability of agent activity.
Key Features
- Run multiple agents in parallel with independent streaming sessions. - Shared memory across agents: decisions and plans from one agent are visible to others. - Local-first storage with on-device embedding and queryable session history.
AI Agent
Agent frameworks, autonomous workflows, and tool-use systems
MCP Server
Model Context Protocol servers, clients, and integrations
AI App
End-user AI applications and AI-native product examples
Developer Tool
Tools that improve coding, testing, build, and local workflow
Download from https://github.com/pacifio/atlas/releases73
Health Score
Active
Commit Activity
May 14, 2026
Created
Aug 15, 2026
Last push
+73
Today's growth
+73
7-day growth
+73
30-day growth
Forks
Open
Watchers
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✓
License
✓
Forked
✓ Active
Maintained
Problem Solved
Atlas solves the problem of agents starting from zero each session and losing context when switching between different coding agents. It also addresses the lack of visibility into agent actions by recording and making queryable all changes, decisions, and history, which is not provided by existing agent tools.
Capabilities
Developers can build complex multi-agent workflows where multiple coding agents collaborate on the same codebase with shared memory and context. They can track every change, query past sessions, and integrate agent knowledge into prompts. The ceiling includes running parallel agent sessions, maintaining a persistent knowledge base, and enabling seamless agent switching without loss of context, suitable for large-scale software projects.
Bottom Line
Atlas is ideal for developers and teams who rely heavily on AI coding agents and need robust tracking, shared memory, and multi-agent coordination. It is not for those who prefer minimal tooling or work with a single agent without need for persistent context. The key trade-off is the added complexity of managing a source-control layer for agents versus the benefit of enhanced continuity and visibility.