What plugs into your local AI runtime. 37 curated apps across 12 categories — chat UIs, coding agents, RAG pipelines, voice, image, browser extensions, editor plugins, mobile + desktop, agent frameworks, productivity, SDK wrappers.
Each entry carries an honest editorial verdict — pros, cons, the runtime it works against, the minimum VRAM, and the privacy posture. Filter to your stack, jump to the detail page, ship.
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4 of 37 apps matching your filters
The default agent framework. Pipelines, retrievers, tool-calling — works against any local backend.
“The default agent framework. Heavy on abstractions, deep ecosystem — pick this if you want defaults.”
RAG-first agent framework. Better defaults than LangChain for doc-corpora work; same local-runtime story.
“Best agent framework for RAG-first workloads. Less abstraction than LangChain.”
Production-leaning multi-agent framework. Role + goal + task — opinionated and ergonomic.
“Best ergonomic multi-agent framework. Picks defaults you'd otherwise have to argue about.”
Microsoft's multi-agent framework. Conversation-first orchestration of role-played agents.
“Best for multi-agent role-played workflows. Niche; not the default agent framework.”
We curate this directory editorially — same review queue as the benchmarks feed. Open an issue with the project link and your one-line pitch for why it belongs.
Editorial review applies — same standards as the rest of the site. We won't list apps that don't actually work against a local runtime, regardless of marketing claims.
The runtime layer: Ollama, vLLM, llama.cpp, MLX, LM Studio server, ComfyUI. What apps in this directory talk to.
Tell us your use case, get a full rig recipe — runtime + models + the apps from this directory that fit your stack.
Match an app's minimum-VRAM requirement to real hardware with our price/perf comparison.
Real operator submissions on the model × hardware × app combos that work. The proof behind the editorial picks.