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AAS Core: review, pricing, security and alternatives

AAS Core is an open-source agent infrastructure component published by sickn33, in the agent infrastructure family. A local agent skill manager with catalog discovery, skill selection, stack validation, and planning capabilities. Its repository has 48,440 stars and its last commit is from October 24, 2026.

Open sourceSelf-hostableActively maintainedLow risk

What AAS Core does

AAS Core belongs to the agent infrastructure family: technical building blocks for agents: memory, execution sandboxes, model gateways, observability, evaluation. On our grid it ranks #10 of the 28 projects of this family listed in the directory.

It is not an agent in itself: it is a component other agents use (memory, isolated execution, web access, model gateway or monitoring). You pick it based on the agent or framework it has to equip.

You use it from: terminal (CLI) and web app. It can run on your own machine or server.

Who is AAS Core for?

It is for teams running agents in production that need a reliable component: isolated execution, memory, model gateway or observability. Typical tasks people give it:

  • isolate code generated by an agent
  • track model call costs and errors
  • give an agent long-term memory

It is a good candidate if you are comfortable in a terminal and your data must stay on your machines.

Access and human control

Its documentation does not detail the access granted to the agent: check the settings before connecting it to your accounts.

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

Drive a web browserDrive a web browser : 7 %7 %Call online services and APIsCall online services and APIs : 11 %11 %
Share of the 28 agents in the family that have each access, according to their documentation. In orange, AAS Core's access.

AAS Core pricing

The code is free, under the MIT licence.

Getting started with AAS Core

  1. Install it: the project ships as a Python package (install with pip or uv). The exact command is in the repository README.
  2. Start with the minimal example from the docs, then add one tool at a time and check what the agent does with it.
  3. Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.

Security: risk level

An infrastructure component sees prompts, keys and data pass through: self-host it or read the service's retention policy.

Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.

Project activity and releases

Created on January 14, 2026, the sickn33/agentic-awesome-skills repository has 48,440 stars, 7,043 forks and 0 open issues, with 3,336 commits in total. It received changes this month.

Over the last 52 weeks: 3,185 commits, an average of 61.3 per week.

Nov 2, : 0 · Nov 2, 2025Nov 2,Nov 9, : 0 · Nov 9, 2025Nov 16, : 0 · Nov 16, 2025Nov 23, : 0 · Nov 23, 2025Nov 30, : 0 · Nov 30, 2025Dec 7, : 0 · Dec 7, 2025Dec 14, : 0 · Dec 14, 2025Dec 21, : 0 · Dec 21, 2025Dec 28, : 0 · Dec 28, 2025Dec 28,Jan 4, : 0 · Jan 4, 2026Jan 11, : 0 · Jan 11, 2026Jan 18, : 23 · Jan 18, 2026Jan 25, : 74 · Jan 25, 2026Feb 1, : 225 · Feb 1, 2026Feb 8, : 96 · Feb 8, 2026Feb 15, : 30 · Feb 15, 2026Feb 22, : 51 · Feb 22, 2026Feb 22,Mar 1, : 96 · Mar 1, 2026Mar 8, : 191 · Mar 8, 2026Mar 15, : 110 · Mar 15, 2026Mar 22, : 134 · Mar 22, 2026Mar 29, : 85 · Mar 29, 2026Apr 5, : 87 · Apr 5, 2026Apr 12, : 86 · Apr 12, 2026Apr 19, : 71 · Apr 19, 2026Apr 19,Apr 26, : 63 · Apr 26, 2026May 3, : 40 · May 3, 2026May 10, : 47 · May 10, 2026May 17, : 39 · May 17, 2026May 24, : 43 · May 24, 2026May 31, : 45 · May 31, 2026Jun 7, : 76 · Jun 7, 2026Jun 14, : 47 · Jun 14, 2026Jun 14,Jun 21, : 96 · Jun 21, 2026Jun 28, : 71 · Jun 28, 2026Jul 5, : 67 · Jul 5, 2026Jul 12, : 60 · Jul 12, 2026Jul 19, : 140 · Jul 19, 2026Jul 26, : 44 · Jul 26, 2026Aug 2, : 65 · Aug 2, 2026Aug 9, : 43 · Aug 9, 2026Aug 9,Aug 16, : 31 · Aug 16, 2026Aug 23, : 40 · Aug 23, 2026Aug 30, : 45 · Aug 30, 2026Sep 6, : 82 · Sep 6, 2026Sep 13, : 47 · Sep 13, 2026Sep 20, : 55 · Sep 20, 2026Sep 27, : 108 · Sep 27, 2026Oct 4, : 141 · Oct 4, 2026Oct 4,Oct 11, : 79 · Oct 11, 2026Oct 18, : 97 · Oct 18, 2026Oct 25, : 115 · Oct 25, 2026Oct 25,
Commits per week on the main repository, last 52 weeks (GitHub API, checked October 25, 2026).

250 releases in total; 30 in the last twelve months. Latest release: v20.0.0, on October 24, 2026.

v19.0.1 · Oct 6, 2026v19.0.1Oct 6, 2026v19.1.0 · Oct 8, 2026v19.2.0 · Oct 9, 2026v19.3.0 · Oct 10, 2026v19.4.0 · Oct 11, 2026v19.5.0 · Oct 12, 2026v19.6.0 · Oct 13, 2026v19.7.0 · Oct 14, 2026v19.8.0 · Oct 16, 2026v19.10.1 · Oct 18, 2026v19.10.0 · Oct 18, 2026v19.9.0 · Oct 18, 2026catalog-v2026.10.19 · Oct 18, 2026v19.11.0 · Oct 19, 2026v19.12.1 · Oct 20, 2026v19.12.0 · Oct 20, 2026v19.13.0 · Oct 21, 2026v19.15.0 · Oct 22, 2026v19.14.0 · Oct 22, 2026v20.0.0 · Oct 24, 2026v20.0.0Oct 24, 2026
The latest 20 releases published on GitHub (hover a point for details).

AAS Core vs other agent infrastructure

GitHub stars of the best-rated open-source projects in the agent infrastructure family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.

OmniRouteOmniRoute : 80.7K80.7KMem0Mem0 : 67.7K67.7KFirecrawlFirecrawl : 194.9K194.9KClaude-MemClaude-Mem : 102.8K102.8KCogneeCognee : 32.7K32.7K9Router9Router : 31.3K31.3KHyperframesHyperframes : 71.3K71.3KCrawl4AICrawl4AI : 86.2K86.2KAAS CoreAAS Core : 48.4K48.4K
Log scale; AAS Core in orange. Checked October 25, 2026.

AAS Core and other agent infrastructure at a glance

The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.

Quick comparison: agent infrastructure
AgentModelScoreStars or entry priceSelf-hostableHuman approval
AAS Coreopen source8248.4K ★yes–
OmniRouteopen source9080.7K ★yes–
Mem0open source8967.7K ★yes–
Firecrawlopen source86194.9K ★yes–
Claude-Memopen source86102.8K ★yes–
Cogneeopen source8532.7K ★yes–
9Routeropen source8531.3K ★yes–
Hyperframesopen source8471.3K ★yes–

How we rated it

Score: 82/100, computed only from public, verifiable data, with no subjective testing or partnership:

  • Adoption 32/40: 48,440 stars on a log scale (40 points from about 200,000).
  • Activity 30/30: last commit less than a month ago, 30 releases in six months, 3,185 commits in a year.
  • Framework 20/30: licence, default human approval, self-hosting, model choice and documentation site.

The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.

Verdict

AAS Core is one of the most solid projects in its family: followed, active and well framed.

Strengths

  • Widely followed: 48.4K stars
  • Very active development
  • Frequent releases (30 in a year)
  • Can run on your side: data under control
  • Permissive licence (MIT)

Frequently asked questions

Is AAS Core free?

The software is free (MIT licence). You still pay for the model calls, unless you use a local model.

Is AAS Core safe?

Our risk level: low. Give it minimum rights and approve irreversible actions.

Which models does AAS Core use?

Its documentation does not specify the supported models.

Can AAS Core be installed on your own server?

Yes, from the sickn33/agentic-awesome-skills repository. Data then stays with you, but security and updates are your job.

What are the alternatives to AAS Core?

In the same family: OmniRoute, Mem0, Firecrawl, and Claude-Mem.

AAS Core or OmniRoute: what is the difference?

Both belong to the agent infrastructure family. AAS Core has 48.4K stars against 80.7K for OmniRoute. The right choice mostly depends on the access you are willing to give it.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score