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A practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and multi-agent architecture. Current trend focus: coding agent containment, emerging agent runtimes, and production AI workflow patterns.

frameworkMDXNOASSERTION
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Stars266
Forks48
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Production readinessExperimentalGrowing but not yet battle-tested at scale.
Risk notesNOASSERTIONVerify license before production use.
AgentHub Score
78 / 100
Composite score from 6 signals. How we score →
Active project
78Score
Growth
84B+
Activity
96A+
Documentation
70C+
Maturity
74B
Community
83B+
Production
58C
GitHub stars · 90 days266 +9.7%
30d90d1y
latest release
Commit activity · 52 weeksActive contributor activity
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Practical assessment
Should you use it?

✓ Best for

  • Multi-agent orchestration
  • Production agentic workflows
  • Stateful long-running tasks

◎ Strengths

  • Stable API
  • Active release cadence
  • Strong GitHub community

✕ Not ideal for

  • Simple single-step automation
  • Teams without Python/ML expertise

⚠ Watch-outs

  • Breaking changes between minor versions
  • Ecosystem lock-in if tightly coupled
Technical details
What's inside
LanguageMDX
LicenseNOASSERTION
Sourcegithub
Open source✗ No
Commercial use
Docs
Demo
Paper

AgentHub Score

78
Score 78/100
Above average

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