Enjambre – a durable kernel for swarms of AI agents (Python, MCP)
enjambre A small, honest operating system for swarms of AI agents. It takes the agents you already have (Claude Code, Codex, a local model behind Ollama, a hosted API, your own scripts) and gives them what a team of processes needs to work together without lying to each other: a kernel, a queue, leases, a permission gate, a router and a shared memory you can see. Español pip install . # from a clone; one dependency (PyYAML) enjambre demo # open http://127.0.0.1:8765 Runs on Linux, macOS and Windows with Python 3.10 or newer; every change is tested on all three.
- ▪enjambre A small, honest operating system for swarms of AI agents.
- ▪It takes the agents you already have (Claude Code, Codex, a local model behind Ollama, a hosted API, your own scripts) and gives them what a team of processes needs to work together without lying to each other: a kernel, a queue, leases, a
- ▪Español pip install . # from a clone; one dependency (PyYAML) enjambre demo # open http://127.0.0.1:8765 Runs on Linux, macOS and Windows with Python 3.10 or newer; every change is tested on all three.
Hacker News (AI / LLM) files mainly under ai. We currently carry 5,696 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/santibccc-sudo/enjambre-os |
| Publication time | Sun, 20 Sep 2026 08:55:30 +0000 |
| Retrieval time | 2026-09-20T09:08:47.265Z |
| Last seen | 2026-09-20T09:08:47.265Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | eG9kKhoiA9pY · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
enjambre A small, honest operating system for swarms of AI agents. Enjambre is Spanish for swarm. It takes the agents you already have (Claude Code, Codex, a local model behind Ollama, a hosted API, your own scripts) and gives them what a team of processes needs to work together without lying to each other: a kernel, a queue, leases, a permission gate, a router and a shared memory you can see. Español pip install . # from a clone; one dependency (PyYAML) enjambre demo # open http://127.0.0.1:8765 Runs on Linux, macOS and Windows with Python 3.10 or newer; every change is tested on all three. The demo needs no model and no API key. Four scripted agents run a small editorial pipeline: research, draft, review, publish. The critic stumbles once so you can watch a retry.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.