macro-inc/macro

Macro is a unified workspace for teams: email, chat, docs, tasks, agents, calls, and CRM — @-linked together with shared AI memory.

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Summary Information

Updated 10 minutes ago
Added to GitGenius on August 13th, 2026
Created on November 8th, 2025
Open Issues & Pull Requests: 53 (+0)
GitHub issues: Enabled
Number of forks: 311
Total Stargazers: 3,133 (+17)
Total Subscribers: 44 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 11.8 hours
Mean response time: 2.3 days
90th percentile: 10.5 days
Tracked items: 25

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. Only 12% of issues opened in the past year have been closed. Three people close 89% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 9
New in 7 days: 11
Closed in 7 days: 11
Avg open age: 6 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 11
Closed in 7 days: 11
Comments in 7 days: 2
Events in 7 days: 7

Top labels

  • planned (3)
  • enhancement (1)

Detailed Description

Macro is an all-in-one workspace that unifies email, chat, documents, tasks, AI agents, calls, and CRM functionality into a single interface with shared team-level memory.

The tool addresses the fragmentation problem that emerges when teams adopt multiple specialized applications like Slack, Linear, Notion, and HubSpot. Rather than integrating separate systems through external connectors, Macro redesigns work software as a unified platform from the ground up. Its architecture uses a bidirectional graph backend where all content—whether from documents, tasks, messages, or emails—shares the same underlying storage, enabling native cross-references and eliminating the need to switch between tools.

Teams should adopt Macro if they want to consolidate their tool stack and reduce context switching. It suits small companies or teams within larger organizations that need a cohesive operating system rather than a collection of point solutions. The tool is built in SolidJS and Rust with emphasis on speed and reliability. Its modular block architecture allows each feature to be purpose-built for its specific function while maintaining integration through the shared backend, making everything @-linked and searchable across the workspace.

The project has been dogfooded internally by a small team over an extended period before public release, indicating substantial real-world validation of the core concept. Development is active with ongoing feature work and a clear focus on building a complete alternative to fragmented tool ecosystems rather than a niche addition to existing workflows.