GraphCanon updated 4w · GitHub synced 4w · 29 views this month
Decision brief
Agently, a Python framework for GenAI app development under Apache-2.0, simplifies agent interaction with structured data and supports model switching without recoding.
Good fit when
- Need to develop applications quickly using various GenAI models like GPT or Gemini without rewrites
- Looking for event-driven flows (*TriggerFlow*) to handle complex logic in GenAI apps
Avoid when
- Do not require flexibility across different GenAI models; specific model commitment is preferred
- *TriggerFlow*'s complexity is too high for very simple use cases or those needing direct simplicity over flow-based control
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (5d since push)
- As of 4w
- Provenance
- Not a fork · Organization account
- As of 4w
- Security (OSV)
- 2 low (2 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install AgentlyHow it fits your stack(7)
Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.
Alternative
Related
Relationship graph
Optional deeper exploration of typed edges and category neighbours.
Similar tools
Same-category neighbours not already linked as typed edges.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Agently is a framework to build GenAI applications easily, with features like interacting with GenAI agents using structured data and chaining calls in event-driven flows.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Jul 21, 2026
Categories
Tags
README
License
Agently follows an open-core model:
- Open-source core: Apache 2.0
- Trademark usage policy: TRADEMARK.md
- Contributor rights agreement: CLA.md
- Enterprise extensions and services: separate commercial agreements
For agents
This page has a .md twin and JSON over the API.