Home/Compare/awesome-llm-apps vs agent-toolkit

Comparison

awesome-llm-apps vs agent-toolkit

Verdict

Pick awesome-llm-apps when license: awesome-llm-apps is Apache-2.0, agent-toolkit is MIT; pick agent-toolkit when license: agent-toolkit is MIT, awesome-llm-apps is Apache-2.0.

Markdown twin · awesome-llm-apps alternatives · agent-toolkit alternatives

GraphCanon updated today

awesome-llm-apps logo

awesome-llm-apps

Shubhamsaboo/awesome-llm-apps

120kpushed Jul 11, 2026
vs
agent-toolkit logo

agent-toolkit

softaworks/agent-toolkit

2.2kpushed Mar 5, 2026

Trust & integrity

Signalawesome-llm-appsagent-toolkit
Maintenance
Very active (3d since push)
As of 1d · github_public_v1
Slowing (131d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of 1d · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 4d · osv@v1
No lockfile (source not queried)
As of today · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

awesome-llm-apps
Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.
agent-toolkit
A curated collection of skills for AI coding agents. Skills are packaged instructions and scripts that extend agent capabilities across development, documentation, planning, and professional workflows

Stars

awesome-llm-apps
120k
agent-toolkit
2.2k

Forks

awesome-llm-apps
18k
agent-toolkit
210

Open issues

awesome-llm-apps
17
agent-toolkit
18

Language

awesome-llm-apps
Python
agent-toolkit
Python

Adopt for

awesome-llm-apps
awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python.
agent-toolkit
-

Persona

awesome-llm-apps
-
agent-toolkit
-

Runtime

awesome-llm-apps
-
agent-toolkit
-

License

awesome-llm-apps
The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license.
agent-toolkit
MIT

Last pushed

awesome-llm-apps
Jul 11, 2026
agent-toolkit
Mar 5, 2026

Categories

awesome-llm-apps
AI Agents, Data & Retrieval
agent-toolkit
AI Agents, Vector Databases

Trust and health

Maintenance

awesome-llm-apps
Very active (96%)
agent-toolkit
Slowing (36%)

Days since push

awesome-llm-apps
3d
agent-toolkit
131d

Open issues (now)

awesome-llm-apps
17
agent-toolkit
18

Owner type

awesome-llm-apps
User
agent-toolkit
Organization

Full report

awesome-llm-apps
Trust report
agent-toolkit
Trust report

Choose awesome-llm-apps if…

  • License: awesome-llm-apps is Apache-2.0, agent-toolkit is MIT.
  • Pricing: Free with open-source licensing, but commercial exploitation is allowed..
  • Tags unique to awesome-llm-apps: agents, applications, customizable, deployable.
  • Also covers Data & Retrieval.
  • When you need quick implementations of various real-world use cases for AI Agents and RAG.

When NOT to use awesome-llm-apps

  • If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch.
  • When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction.

Choose agent-toolkit if…

  • License: agent-toolkit is MIT, awesome-llm-apps is Apache-2.0.
  • Tags unique to agent-toolkit: agent-skills, ai, automation, claude.
  • Also covers Vector Databases.

When NOT to use agent-toolkit

  • Last GitHub push was 131 days ago (slowing maintenance, Mar 5, 2026). Validate activity before betting a new project on agent-toolkit.
  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: awesome-llm-apps 120k · agent-toolkit 2.2k (synced Jul 14, 2026).

Common questions

What is the difference between awesome-llm-apps and agent-toolkit?
awesome-llm-apps: Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.. agent-toolkit: A curated collection of skills for AI coding agents. Skills are packaged instructions and scripts that extend agent capabilities across development, documentation, planning, and professional workflows. See the comparison table for live GitHub stats and shared categories.
When should I choose awesome-llm-apps over agent-toolkit?
Choose awesome-llm-apps over agent-toolkit when License: awesome-llm-apps is Apache-2.0, agent-toolkit is MIT; Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; Also covers Data & Retrieval; When you need quick implementations of various real-world use cases for AI Agents and RAG.
When should I choose agent-toolkit over awesome-llm-apps?
Choose agent-toolkit over awesome-llm-apps when License: agent-toolkit is MIT, awesome-llm-apps is Apache-2.0; Tags unique to agent-toolkit: agent-skills, ai, automation, claude; Also covers Vector Databases.
When should I avoid awesome-llm-apps?
If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction.
When should I avoid agent-toolkit?
Last GitHub push was 131 days ago (slowing maintenance, Mar 5, 2026). Validate activity before betting a new project on agent-toolkit. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Is awesome-llm-apps or agent-toolkit more popular on GitHub?
awesome-llm-apps has more GitHub stars (119,936 vs 2,190). Stars measure visibility, not whether either tool fits your constraints.
Are awesome-llm-apps and agent-toolkit open source?
Yes - both are open-source projects on GitHub (awesome-llm-apps: Apache-2.0, agent-toolkit: MIT).
Where can I find alternatives to awesome-llm-apps or agent-toolkit?
GraphCanon lists graph-backed alternatives at awesome-llm-apps alternatives and agent-toolkit alternatives (awesome-llm-apps markdown twin, agent-toolkit markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, awesome-llm-apps or agent-toolkit?
awesome-llm-apps: Very active. agent-toolkit: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for awesome-llm-apps and agent-toolkit?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-llm-apps trust report; agent-toolkit trust report.

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