Agent-Field/agentfield
Build, run and scale AI agents like API and microservices
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
Ranks #14 among AI Agents repositories tracked this week, and #12 over the last 30 days; #711 of 3,103 repositories GStars tracks this week (top 23%).
5 releases in the last 90 days, the latest 7 days ago, with 62 contributors on GitHub.
Peaked at #37 in the weekly ranking the week of Mar 29, its best in the past year.
Use Cases & Benefits
- Build, run, and scale AI agents as callable APIs with production infrastructure for routing, async execution, memory, and cryptographic audit trails.
- Provides a secure, scalable AI backend with cryptographic agent identities, verifiable credentials, and built-in governance for traceable, tamper-proof AI workflows.
- Use for deploying complex multi-agent AI systems that require durable async execution and human-in-the-loop approval in backend services.
- Use for orchestrating AI-powered workflows with cross-agent calls, automatic discovery, and structured AI outputs in Python, Go, or TypeScript.
- Use for managing AI agent fleets with canary deployments, observability dashboards, and policy enforcement in cloud-native or Kubernetes environments.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
AI has outgrown chatbots and prompt orchestrators. Backend agents need backend infrastructure.
AgentField is an open-source control plane that makes AI agents callable by any service in your stack - frontends, backends, other agents, cron jobs - just like any other API. You write agent logic in Python, Go, or TypeScript. AgentField turns it into production infrastructure: routing, coordination, memory, async execution, and cryptographic audit trails. Every function becomes a REST endpoint. Every agent gets a cryptographic identity. Every decision is traceable.
What you just saw:
app.ai()calls an LLM and returns structured output.app.pause()suspends for human approval.app.call()routes to other agents through the control plane.app.run()auto-exposes everything as REST. Read the full docs →Build - Python, Go, or TypeScript. Every function becomes a REST endpoint.
Run - Production infrastructure for non-deterministic AI.
Govern - IAM for AI agents. Identity, access control, and audit trails - built in.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+216 stars over 85 days across 14 snapshot days; best day +20 on Jul 21.
Forks
430+47
Open issues
36-36
Compared with peers in AI Agents
Fastest-growing repositories GStars tracks in this cohort for the week of Oct 18, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| morluto/rea | 373.3K | +88.2K | 60 | 5 days ago |
| DietrichGebert/ponytail | 174.8K | +9.9K | 75 | 7 days ago |
| stablyai/orca | 103.9K | +9.5K | 40 | today |
| affaan-m/ECC | 287.3K | +6.4K | 64 | 22 days ago |
| Leonxlnx/taste-skill | 101.6K | +3.8K | 75 | 3 days ago |
| Agent-Field/agentfield | 2.6K | +0 | 65 | 7 days ago |
| Category median | 174.8K | +9.5K | 64 | — |
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