emanuele-web04/synara

The best place to build with your AI sub

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Summary Information

Updated 59 minutes ago
Added to GitGenius on August 31st, 2026
Created on March 27th, 2026
Open Issues & Pull Requests: 225 (+0)
Number of forks: 248
Total Stargazers: 1,627 (+0)
Total Subscribers: 8 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 29.2 hours
Mean response time: 8.3 days
90th percentile: 23.0 days
Tracked items: 175

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 99% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 14% of tracked open issues have had no activity in three months. Only 13% of issues opened in the past year have been closed. Three people close 87% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 88
New in 7 days: 28
Closed in 7 days: 23
Avg open age: 55 days
Stale 30+ days: 38
Stale 90+ days: 10

Recent activity

Opened in 7 days: 22
Closed in 7 days: 23
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • needs-triage (76)
  • bug (53)
  • enhancement (23)

Detailed Description

Synara is a platform for building applications with AI agents.

The tool addresses the challenge of integrating AI agents into applications by providing a dedicated environment where developers can construct and deploy agent-based systems. It offers a structured approach to working with AI agents, handling the complexity of agent orchestration and interaction patterns so developers can focus on application logic rather than infrastructure concerns.

Synara suits teams building agent-driven applications who want a managed platform rather than assembling components themselves. The project is particularly relevant for developers seeking to move beyond simple chatbot interfaces toward more sophisticated multi-agent systems. The README does not compare the tool to specific alternatives, so adoption decisions should rest on whether the managed platform approach aligns with your team's architecture preferences and whether the tool's feature set matches your agent complexity requirements.

The project shows active development with regular commits across multiple areas of the codebase. Work spans both core functionality and documentation, indicating sustained attention to both the platform itself and developer experience. The repository maintains a focused scope rather than attempting to be a catch-all framework, with changes concentrated on specific capabilities rather than scattered across numerous unrelated features.