CrabTalk is an open-source agent daemon written in Rust. Five megabytes, zero children, nothing hidden — just the plumbing every agent app rebuilds, written once and shared.
curl -sSL https://crabtalk.ai/install | sh 
One command launches the daemon and drops you into a session. No server to provision, no config to author, no dashboard to sign into. The binary is five megabytes; it holds nothing back.
Crashes don’t propagate. Topics route themselves. Memory stays precise. Coordination scales. Each one a pillar — drawn here as a live plate.
In most AI systems, one tool crashes and the whole chat crashes with it.
CrabTalk runs every tool, every command, every extension in its own space. One breaks; the rest keep going.
Fig. 01. Broken parts, stable core. A central body holds; satellites move on their own orbits, breaking apart and re-forming without disturbing the centre.
Fig. 02. Topic lanes. Messages travel along their own subject channels — work in the work lane, home in the home lane — without per-window juggling.
Other AI makes you open a new chat per subject.
CrabTalk sorts by topic itself — work stays in the work channel, home switches itself, no window-juggling.
Fig. 03. Indexed retrieval. A bound archive built on the same internals engineers trust for their databases — fast lookup that doesn’t slow as it grows.
AI memory usually forgets fast, or slows to a crawl as it grows.
We ported the internals of SQLite to the recall layer — accurate, fast to query, compact on disk.
Fig. 04. At scale. Hundreds of agents in coordinated motion — a conductor facing a full orchestra, each section playing its own line on cue.
Other systems may cap around 10 concurrent agents.
CrabTalk is designed to coordinate 10,000. A conductor facing a full orchestra, not a small ensemble.
Fig. 05. One conversation, two voices. A guest agent speaks directly into the shared history — tagged, not delegated — then the primary resumes on the next turn.
Sometimes a second agent should speak into an ongoing conversation — a reviewer, a translator, an expert.
A guest reads the shared history, adds a tagged message, and steps back. The primary picks up where it left off.