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dowse

by ltspaceversion 0.10.0i★ –iRuns on your computer
Registry nameio.github.ltspace/dowse

Install

Overview

Description from the maker (original English)

Fast local full-text search for Windows files (tantivy + jieba), exposed to AI agents over MCP.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

The maker has not listed install details in the registry. See the maker’s README below.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account ltspace, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7259 servers in this category
  • Published to the registry more recently than 24% of the other 7259 servers in this category
  • Basic checks equal to or better than 100% of the other 7259 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is dowse safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.10.0) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Rust on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

English | 简体中文 | 日本語 | 한국어 | Español | Italiano

dowse

Open-source local file content search for Windows. Find file names, PDF and Office contents, source code, and text inside screenshots — one hotkey away.

Website · English product page · Windows file-content search guide(中文)

The name comes from a dowsing rod.

Motivation

No Windows tool satisfies all three of the following at once:

  • Keep a persistent index of file contents, not just file names (Everything can scan contents on demand, but its instant index is centered on names and paths)
  • Recognize and index text inside images on ordinary Windows PCs without requiring a Copilot+ device
  • One hotkey to summon, full keyboard operation, no perceptible latency

The closest open-source implementation is sist2, but it targets Linux (on Windows it only runs via Docker), treats Chinese text as trigrams, and the project is no longer maintained. dowse is a Windows-native implementation built around these three points.

Features

🔍 File name searchInstant, as you type
📄 Document content searchPlain text, Markdown, code, and document formats (PDF, Word, Excel, PowerPoint)
🖼️ Screenshot / image OCRText inside PNG/JPG/WebP/BMP images, fully offline (Windows.Media.Ocr)
🈶 Chinese word segmentationjieba + BM25 ranking, not trigrams — plus automatic GBK encoding detection
⚡ Incremental indexingFile-watch during runtime, mtime/size reconciliation at startup
🤖 MCP serverExposes local search to AI agents over stdio
🚀 NTFS fast pathMFT enumeration + USN Journal, admin-only, falls back transparently otherwise

dowse vs. the alternatives

dowseEverythingWindows Searchsist2
File name search✓✓✓✓
Document content search✓ (persistent index)on-demand scandepends on indexed locations and filters✓
Screenshot / image OCR✓✗device/version dependentlimited (optional Tesseract)
Proper Chinese segmentation✓ (jieba)—limited✗ (trigrams)
Fully local, no network✓✓✓✓
Global hotkey overlay✓✓✓ (Win key)✗ (web UI)
Windows-native✓✓✓✗ (Linux-first, Docker on Windows)

Chinese text handling

  • Word segmentation via jieba, ranking via BM25 (tantivy engine). No trigrams.
  • Automatic file encoding detection (chardetng). GBK-encoded files are decoded correctly before indexing — this matters because a large share of Chinese-language documents on Windows, especially older ones, are still saved in GBK rather than UTF-8, and a search tool that assumes UTF-8 will silently mis-index or garble them.
  • Multi-term queries default to AND semantics. Quoted phrase queries match on exact position. Inline operators narrow things down further: path:reports, mtime:>2026-01-01, size:>10mb, uppercase OR between groups, -term to exclude.
  • OCR runs on the Windows-native engine (Windows.Media.Ocr), fully offline. The zh-Hans language pack also covers mixed Chinese/English text, no extra configuration required.

Performance

Design targets; exceeding them is treated as a defect. "Measured" is a from-scratch benchmark of dowse 0.7.0 (i7-13700K / 24 logical cores / 64GB RAM, single machine, single session, 2026-07-12), reusing the byte-identical corpus from the v0.6.1 round-3 benchmark for direct comparability. Full raw output (index/search logs, JSON result files) is kept with the benchmark working directory, outside this repo.

MetricDesign targetMeasured (v0.7.0, 2026-07-12)
Hotkey to window visible< 50msnot measured — CLI-only benchmark, no overlay-app instrumentation
Keystroke to results rendered< 80msnot measured — same
OCR, single image~112ms / 1080p screenshot~170ms isolated (480×200 synthetic image), unchanged from v0.6.1 — the OCR pipeline was not modified this release. Sub-30ms readings on immediate repeat runs of the same image reflect OS-level recognition caching, not real recognition, and are excluded here. Not real 1080p screenshots
Resident memory< 150MB idlenot measured (idle); peak working set during full-corpus indexing was ~327MB — a different metric, not a regression against the idle target
Installer size< 50MB (revised 2026-07 — the original 15MB target predates the bundled CLI sidecar)14.98MB (dowse-app_0.9.0_x64-setup.exe, published release)
Full-text index build, 10,000 files / 437MBseconds (planned filename-only fast path)10.0–10.6s — current full-content dowse index, not the planned filename-only MFT path
Full-text index build + OCR, 15,100 files (incl. 5,100 images)—~46.6s first pass, all 5,100/5,100 images OCR'd in that same pass — no pending, no second pass needed
Search latency, P50 (5 required categories)—30.7–161.1ms across single word / Chinese phrase / English phrase / multi-word AND / zero-result, on a 15,100-document index
Search latency, P95—39.1–172.3ms, same 5 categories
ext: filter query latency—P50 155.6ms, same band as the non-zero-result query categories
Index size ÷ corpus size—0.36 (text-only), down from 0.54 in the v0.6.1 round

Full-corpus rows measured on the same 10,000-file / 437.66MB text corpus plus 5,100 synthetic 480×200 OCR images (89.8MB) used for the v0.6.1 round-3 numbers above — byte-identical, reused directly rather than regenerated. Indexing is roughly 2x faster and the on-disk text index roughly a third smaller than v0.6.1; both track the new tokenizer (lowercase normalization, alphanumeric-boundary splitting of Latin words) producing a leaner term dictionary. The zero-result query dropped from 135ms (v0.6.1) to a startup-noise-level 31ms, consistent with less index to scan before concluding a term is absent. OCR recognition speed is unchanged this release, since the pipeline was not touched: single-image recognition stays around 170ms, and the sub-30ms readings on repeated identical images are OS-level caching artifacts, not real recognition. The full-corpus text-plus-OCR pass got faster (83s to 46.6s) from the quicker tokenizer and write path, not from faster recognition.

Quick start

Download — grab the installer from the latest release (dowse-app_*_x64-setup.exe), run it, then Alt+\` to summon.

The installer is unsigned, so Windows SmartScreen will flag it on first run. To proceed, click More info and then Run anyway. A code-signing certificate is a recurring cost that is hard to justify for an independent project; it may be reconsidered for a future release.

Install the CLI — the library and command-line tool ship as one dowse package:

cargo install dowse                 # once published to crates.io

cargo install --path crates/dowse # from a local checkout

Build from source:

git clone https://github.com/ltspace/dowse && cd dowse

CLI

cargo run -p dowse -- index D:\docs # build the index cargo run -p dowse -- search 限流 # search cargo run -p dowse -- search "精确短语" # phrase query cargo run -p dowse -- add E:\projects # add another root incrementally (no full rebuild) cargo run -p dowse -- rules show # view index rules (excluded dirs, extra extensions, size cap)

Overlay app (Tauri 2 + Svelte 5)

cd crates/dowse-app npm install cargo tauri build # produces the installer under target/release/bundle

Overlay app: Alt+\ to summon, ↑↓ to select, Enter to open, Ctrl+Enter to reveal in Explorer, Ctrl+C to copy path, Esc to hide. Results are paginated in groups of 50; the compact ‹ 1 / N › control shows only when needed, and pressing ↓ past the last result or ↑ before the first moves between pages. Two nearly invisible dropdowns sit at the right of the search bar — file type filter (Ctrl+P) and sort order (Ctrl+S, relevance / newest / oldest / largest); both stay faint until you select a non-default value. Right-click a result row for a native Explorer-style context menu (open / reveal in folder / copy path / copy name). A pin toggle at the top-right keeps the window open when it loses focus (session-only, resets on restart). With an empty input, the overlay lists your recent searches (last 10, stored locally) — ↑↓/Enter to reuse one, Delete to remove it. Ctrl+,` opens the settings panel — general (hotkey rebinding, autostart, interface language) and index rules (excluded directories, extra text extensions, per-file size cap).

MCP server

dowse mcp starts a read-only MCP server over stdio, exposing the local index to AI agents:

claude mcp add --scope user dowse -- dowse mcp

Four tools: search (query, bounded limit / offset, sort by relevance / mtime / size, comma-separated ext filter, and a total_hits count), preview (long context + metadata for one hit), read_file_chunk (bounded, paginated text from the indexed snapshot), and index_status (document count, index health, active index rules). The server never touches the index writer or opens arbitrary paths — it only reloads the reader before each call, so it can run alongside the overlay app or a live dowse watch session without write contention.

Architecture

                 ┌─────────────────────────────────────────┐

│ dowse │ │ library core: tantivy index · jieba │ │ segmentation · encoding detection · │ │ text extraction (txt/md/pdf/code/ │ │ docx/xlsx/pptx) · OCR pipeline │ │ ───────────────────────────────────── │ │ CLI + MCP

Only the beginning is shown; read the rest in the repo

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