# Chaty > Private, on-device AI desktop app — GGUF (llama.cpp) & MLX models, a local coding agent, RAG knowledge base, Deep Research, vision and voice. 100% offline, no account, no telemetry. Windows & macOS. - **Type:** MCP server - **Install:** `agentstack add mcp-fangyuan025-chaty` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [Fangyuan025](https://agentstack.voostack.com/s/fangyuan025) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [Fangyuan025](https://github.com/Fangyuan025) - **Source:** https://github.com/Fangyuan025/Chaty - **Website:** https://chaty.ca ## Install ```sh agentstack add mcp-fangyuan025-chaty ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About **English** · [简体中文](README.zh-CN.md) # Chaty ### Private, on-device AI — your models, your data, your machine. Chaty runs open LLMs **100% offline** in a polished desktop app. No account, no cloud, no telemetry — with a local coding agent, a document knowledge base, Deep Research, and hands-free voice built right in. [](../../releases/latest) [](../../releases) [](../../actions) [](../../releases) [](../../releases) [](https://chaty.ca) [](#architecture) [](LICENSE) [**↓ Download**](../../releases) · [**Website**](https://chaty.ca) · [**Docs**](https://chaty.ca/docs.html) · [**Chaty model on Hugging Face**](https://huggingface.co/stevenpr/chaty-qwen3.5-4b-design-GGUF) A local coding agent — searches GitHub, reads the source, edits your files, and runs the tests. **All on your machine.** --- ## Why Chaty - 🔒 **Truly private** — every model, document, and conversation stays on your device. No sign-up, no server, nothing phoned home. - ⚡ **Native and fast** — a Rust + llama.cpp core with **Vulkan / Metal** GPU offload that auto-tunes to your hardware and falls back gracefully to CPU. - 🧰 **More than a chat box** — a coding agent, a knowledge base (RAG), Deep Research, hands-free voice, and a self-healing Design Canvas — all offline. - 🧠 **Runs almost anything** — Llama 3, Gemma 3 / 4, Qwen 3 / 3.5 / 3.6, *any* GGUF from Hugging Face — and **MLX models natively on Apple Silicon** — plus **Chaty's own fine-tuned model**. - 💻 **Friendly to modest hardware** — a first-launch *“Set up for me”* picks a model sized to your RAM and downloads it in one click. ## A local coding agent Flip the **Chat · Code** switch and Chaty becomes an agent for your codebase. Point it at a folder, describe the task, and it explores, edits, and verifies the project by itself — every step shown live, every change behind an approval + diff. - 🌐 **The whole web as a tool** — key-less search of **GitHub** (repos, issues, *and code*), Reddit, YouTube, Bilibili, and any domain; fetching adapts to the content (articles → Markdown, PDFs → text, videos → transcripts). - 🧭 **Drives a real browser** — opens pages, reads dynamic content as text, clicks and fills whole forms with real mouse events, logs in and paginates — and *looks* with the vision model when it matters. - 🧠 **Tools that do the thinking** — `understand_repo` orients in one call, `search_code` ranks files by relevance, `read_file` lifts a single symbol plus its call sites, `validate_change` runs just the tests the change touches. Small models spend their steps on decisions, not grunt work. - ✏️ **Precise edits, real shell** — exact-string patches behind a diff preview with a **syntax gate**, plus commands and long **background jobs** (dev servers, builds) sandboxed to the workspace. - ⏪ **You stay in control** — per-action approval, a command allowlist, prompt-injection defense on everything it reads, and **one-click checkpoint rewind** that restores files *and* rolls back the conversation. - 🔌 **MCP, sized for small models** — connect any Model Context Protocol server (stdio or streamable HTTP), or one-click a **curated, version-pinned store entry** that's live-certified against Chaty's own client. Tool docs are synthesized lean so a 16K context fits as many servers as you like; every result is injection-defended and untrusted servers need per-call approval. - 📚 **Skills & project memory** — drop a `SKILL.md` of procedural steps in `~/.chaty/skills/` (or per-project) and the agent loads it only when relevant; `remember` saves non-obvious findings to `.chaty/memory/` so the next session starts knowing them. Plain markdown, human-editable, never leaves the machine. More Code-mode details - Reads **PDF / Word / Excel / PowerPoint** (scanned PDFs get OCR'd); `search_files` finds by name or content; file outlines navigate big files; failed patches get “did-you-mean” hints. - Browser automation is verified end-to-end against real sites, and can run in your real Chrome — watch it work, logins and all. - Built for local models: an **Off / Normal / Deep** reasoning switch, a **prompt-processing progress ring**, a context-usage ring with automatic compaction, whole-file reads sized to your context window, ranked `search_code` + knowledge-base `search_docs`, and loop-breaking for repetitive small models. - Persistent sessions, project memory (**AGENTS.md**), custom **/skills**, and slash commands. - Tune it under **Settings → Code**: step limit, command timeout, step temperature, an auto-approve-edits toggle, a headless-browser toggle, and a command allowlist. - File access never leaves the folder you pick; out-of-workspace access asks per folder; a `sudo` command asks first with a secure password prompt; downloads land in the workspace and are covered by checkpoints too. ## Benchmarks One local model for every row — **Qwen3.5-35B-A3B** (MoE, ~3 B active per token), mxfp8 on MLX, reasoning off, entirely on one machine: | SWE-bench Verified — 45-task macOS-validated subset | Resolved | | --- | --- | | **Chaty agent (v1.9)** — the full tool loop, 16K context | **15/45 (33 %)** | | qwen-code 0.20 — the model family's own CLI (needs 32K) | 12/45 (27 %) | | pi 0.81 — minimal 4-tool agent CLI | 10/45 (22 %) | | opencode 1.18 | 7/45 (16 %) | | bare bash agent — single-tool ablation | 6/45 (13 %) | Same model, same tasks, same grading, one machine — five agent designs. Chaty leads the field, including the model family's own first-party CLI ([qwen-code](https://github.com/QwenLM/qwen-code)) while using **half its context window**, and resolves **2.5×** the bare-bash ablation. That's the design thesis measured: with frontier models a thin scaffold is enough — on small local models, the intelligence has to live in the tools (repo-aware search, symbol reads, precise edits, recovery guards, post-edit diagnostics). Methodology, per-agent configs, and honest-comparison notes (subset, macOS harness — *not* comparable to leaderboard numbers): [docs/BENCHMARKS.md](docs/BENCHMARKS.md). ## Design Canvas - **Preview | code, side by side** — every page opens as a split studio: live preview left, the **actual source** right, syntax-highlighted and palette-following. Three drag-resizable columns, fullscreen, page reload, and a **Console** tab for the page's logs and errors. - **Point at what you mean** — Inspect links the panes both ways: hover an element and the code jumps to its line; click a code line and the element flashes. **Click to select** (⌘/Ctrl multi-select) and your next instruction edits exactly those elements — or open the source yourself with the **Edit** button. - **Watch the edit happen** — iterations stream in Cursor-style: the code pane scans the document line by line and lands on a **Changes** diff (+N/−N, same language as Code mode). - **Self-healing, persistent** — runtime errors offer a one-click **Fix** (always asks first); a compat layer keeps browser-clean pages clean here too (history API, cookies, clipboard); and each reply keeps its canvas session across close/reopen, with version history, a confirmed reset, and export to a standalone `.html`. ## Chat that renders everything - A streaming, foldable **``** panel that follows the model's reasoning as it generates. - **KaTeX** math, tables, **Mermaid** diagrams, per-block code copy, and in-app rendering of single-file HTML — including playable web games. - A **⌘K command palette**, pinnable / renameable conversations, drag-and-drop attachments, export (Markdown / JSON), and full-text search. - Four palettes (two dark, two light) with system-theme following, native UI zoom, reduced-motion support, and an **English / 简体中文** UI. ## Chaty can see Load a **vision model** (its weights and `mmproj` encoder live together in one folder, paired automatically) and image understanding turns on everywhere: - **Chat** — attach a picture and ask about it; follow-ups stay fast (already-seen images aren't re-encoded). - **Code** — the agent reads screenshots and can look at any image with `view_image`; the composer takes images and documents just like chat. - **Knowledge base** — imported images get a written description beside their OCR text, so search finds what's *in* them; images embedded **inside** PDFs, Word, Excel and PowerPoint files are extracted and described too. - **Canvas** — the model sees the live rendered page when you ask for an edit. Text-only models keep the OCR path, so nothing regresses — and updating from an older version, a one-time prompt tidies your existing loose `.gguf` files into the one-folder-per-model layout with a single click. ## Models: the store, native MLX — and Chaty's own - A built-in **model store**: search Hugging Face by name or author, filter **GGUF / MLX**, sort by trending or downloads — then pick a **quantization** from a dropdown and hit download. Models, not file lists. - Parameter / architecture / vision badges, the repo's README rendered in-app, and a **"fits fully in memory"** hint sized to your machine. Vision models fetch their encoder automatically; pasting a repo link still works. - **MLX runs natively** on Apple Silicon: mlx-community folder models load through Apple's MLX stack in an isolated sidecar — same chat, vision, reasoning controls, Code agent and knowledge-base support as GGUF, and ejecting a model *always* returns its memory. - **Chaty's own fine-tune** — a Qwen3.5-4B distilled from a much larger teacher for leaner on-device single-file web design, with a baked-in Chaty identity and grounded citations. A one-click pick in *“Set up for me”*, fully open on **[Hugging Face](https://huggingface.co/stevenpr/chaty-qwen3.5-4b-design-GGUF)**. ## A private knowledge base - Index **PDF, Word, Excel, Markdown, ~90 text/code formats, and images** into an on-device store — one file or a whole folder. Images are read by **OCR *and*, with a vision model, described in words** so you can search what's *in* the picture. - **Hybrid retrieval**: bge-m3 vectors + BM25 keywords, fused with RRF, de-duplicated with MMR, expanded with neighbors. - **Strict grounding** — answers come only from your files, with **per-file citations** and hover-preview of the source passage. Chaty says when something isn't covered instead of guessing. - **One-click report** — a cited, NotebookLM-style overview of the whole base, exportable to PDF or Markdown. ## Deep Research & the web - Give a topic and Chaty plans queries, runs **multiple rounds** of web search interleaved with reasoning, and writes a structured, cited report — **exportable to PDF or Markdown**. - Honest by design: the reference list contains only sources it actually cited. - A free, key-less, multi-provider search chain (Brave → Bing → DuckDuckGo → Wikipedia) so one blocked provider never breaks search. ## Hands-free voice - **Live mode** — continuous, hands-free conversation with an animated orb. - Voice in/out with silence auto-send and read-aloud — **11 voices** with speed control. - **Deep-dive podcast** — turn your knowledge base into a NotebookLM-style two-host audio show, with WAV export. - All voice runs on the **CPU**, so it never competes with the LLM for VRAM. ## Everything stays on your machine - Conversations, models, and indexes live in one **local data folder** — copy it to back up, clear it in a click. - **GPU acceleration**: cross-vendor **Vulkan** (Windows) and **Metal** (Apple Silicon, offload-all on unified memory), VRAM-aware auto-tuning with OOM back-off and CPU fallback. - **Any `.gguf` — or MLX folder** — tokenizer and chat template come from the model itself; first-class handling for Llama 3, Gemma 3 / 4, and Qwen 3 / 3.5 / 3.6. - **Adjustable context** that auto-fits the model's trained length to your memory and summarizes older turns near the limit; **safe model switching** and full sampling controls with saveable presets. > **Offline-first.** The network is used only for optional web search and one-time model downloads. ## Install Grab the latest build from the [**Releases**](../../releases) page: | Platform | File | Notes | |---|---|---| | Windows x64 | `Chaty_*_x64-setup.exe` | Per-user installer — no admin required | | macOS (Apple Silicon) | `Chaty_*_aarch64.dmg` | See the first-launch note below | **macOS first launch.** Chaty is ad-hoc signed but not notarized (there's no paid Apple Developer account behind it), so Gatekeeper warns on first open. The app is safe — everything runs locally. Clear the download quarantine once: ```sh xattr -dr com.apple.quarantine /Applications/Chaty.app ``` then open Chaty normally. (Or: open it, dismiss the warning, and choose **System Settings → Privacy & Security → Open Anyway**.) On macOS the writable models folder lives in app data — use **Open models folder** in the model menu. ## Build Full details in **[BUILD.md](BUILD.md)**. ```powershell # Windows npm install .\dev.ps1 # dev npm run tauri build -- --no-bundle # release exe → compile the Inno installer ``` ```bash # macOS (Apple Silicon) npm install npm run tauri dev # dev (Metal) npm run tauri build # → .app + .dmg ``` Releases are produced by CI: bump with `scripts/bump-version.sh x.y.z`, then push a `vx.y.z` tag — GitHub Actions builds both installers onto a single release. ## Architecture | Layer | Stack | |---|---| | Shell | Tauri 2 — system tray, global shortcut, single-instance | | Frontend | React 19 · Vite · react-markdown · KaTeX | | Inference | Rust · `llama-cpp-2` (llama.cpp) — Vulkan (Windows) / Metal (macOS) · MLX via an `mlx-swift-lm` sidecar (Apple Silicon) | | Voice | `sherpa-rs` (ONNX Runtime, CPU) — Whisper-base.en + Kokoro-82M | | Knowledge base | bge-m3 embeddings + BM25 · hybrid RRF / MMR retrieval · SQLite vector store | | Storage | SQLite — conversations, messages, full-text search | ## License MIT — see [LICENSE](LICENSE). Built with [llama.cpp](https://github.com/ggml-org/llama.cpp), [Tauri](https://tauri.app), and [sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx). ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [Fangyuan025](https://github.com/Fangyuan025) - **Source:** [Fangyuan025/Chaty](https://github.com/Fangyuan025/Chaty) - **License:** MIT - **Homepage:** https://chaty.ca Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-fangyuan025-chaty - Seller: https://agentstack.voostack.com/s/fangyuan025 - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. 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