Nab

nab

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Token-optimized web fetcher + multilingual ASR + URL watcher. MCP 2025-11-25 compliant. Rust. macOS arm64 first, cross-platform.

nab is a single Rust binary that does three things very well: it fetches any URL as clean markdown (with your real browser cookies and anti-bot evasion), it analyzes any audio or video file with on-device multilingual ASR and speaker diarization, and it watches any URL for changes and pushes notifications when content moves. Everything runs locally. There are no API keys to set up by default. The output is shaped for LLM context windows.

Why nab

• Token-lean by design. nab returns only what an LLM actually needs — clean markdown, BM25-lite query-focused extraction, and structure-aware token budgets — cutting the token cost of web research instead of dumping raw HTML into your context window.
• Multimodal, fully on-device. Transcribe and diarize any audio or video (FluidAudio / Parakeet TDT v3 on the Apple Neural Engine — 131× realtime on a 2-hour clip, 25 EU languages, word-level timestamps, optional Qwen3-ASR for zh/ja/ko/vi) and OCR images via Apple Vision (15 languages, ~10–50 ms). No cloud, no API keys.
• Authenticated reach. Real browser cookies, 1Password auto-login with TOTP/MFA, WebAuthn passkeys, fingerprint spoofing and WAF evasion — reach internal dashboards, SaaS apps, and paywalled research with the same command as a public URL.
• Watch the web. Subscribe to any URL via MCP resources — conditional GETs, semantic diff, adaptive backoff. RSS for the entire web.
• Prompt-injection defense, on by default. Hidden instructions addressed to your AI are surfaced to you, not silently executed by your model — see [Security](#security-prompt-injection-defense).

Everything is a single local Rust binary. No cloud backend, no API keys by default, output shaped for LLM context windows.

Quick start

Tell your AI assistant (recommended):

> Read https://github.com/MikkoParkkola/nab and install nab as my web fetching and audio analysis MCP server

Your agent will install the binary, wire itself up, and start fetching. Works in Claude Code, Cursor, Windsurf, and any AI with terminal access.

Or install and try manually:

brew install MikkoParkkola/tap/nab                            # install
nab fetch https://news.ycombinator.com                        # fetch as markdown
nab models fetch fluidaudio                                   # download ASR model
nab analyze interview.mp4 --diarize                           # transcribe + identify speakers
nab watch add https://status.openai.com --interval 5m         # subscribe to changes

Features

| Command | What it does | |---------|--------------| | nab fetch | Fetch any URL as clean markdown. HTTP/3, browser cookie injection (Brave / Chrome / Firefox / Safari / Edge / Dia), 1Password auto-login, fingerprint spoofing, fetch-time YARA-X redaction for prompt-injection/exfil signatures, 12 site providers. MCP fetch also supports query-focused extraction, readability, and token budgets. | | nab browser | Explicit opt-in browser rendering for JS-heavy pages through a configured Chrome DevTools Protocol WebSocket endpoint. No Chromium is bundled and default nab fetch never auto-launches a browser or remote provider. | | nab analyze | Transcribe and diarize. FluidAudio (Parakeet TDT v3) on Apple Neural Engine, 131x realtime on a 2-hour clip, word-level timestamps, 25 EU languages, optional Qwen3-ASR for zh/ja/ko/vi, optional active reading via MCP sampling. | | nab watch add | Monitor a URL and push notifications via subscribable MCP resources. RSS for the entire web. Conditional GETs, semantic diff, adaptive backoff. | | nab models fetch | Persistent install of inference model binaries. Supports fluidaudio (default on macOS Apple Silicon), sherpa-onnx (cross-platform Parakeet TDT, ~30× realtime CPU), and whisper (universal fallback, whisper-large-v3-turbo, 99 langs). | | nab-mcp | MCP 2025-11-25 server. stdio + Streamable HTTP. 12 tools, 4 prompts, 2+N resources, structured logging, sampling, roots, elicitation. | | nab::content::ocr | Apple Vision OCR engine. 15 languages. Apple Neural Engine accelerated. ~10-50 ms per image. macOS only. |

Security: prompt-injection defense

Web pages increasingly carry instructions written for the AI, not for you — concealed in HTML comments, display:none / aria-hidden text, data-ai / data-mcp / data-agent attribute payloads, or WebMCP manifests. Fetch such a page with a naive tool and those hidden instructions land straight in your model's context, where they can be acted on. This is the prompt-injection-as-phishing class of attack.

nab treats every fetched page as hostile input and runs two local, non-networked guards before any content reaches your agent — on by default, no flag, no setup:

• Secure Ingestion guard — detects and strips machine-targeted markup that is invisible to humans (AI-addressed comments, hidden display:none / aria-hidden text, agent-only data-* payloads, WebMCP advertisements) and reports each detection at Info / Warn / Block severity, so you see what a page tried to tell your agent instead of it being silently executed.
• YARA-X signature guard — scans every returned body for prompt-injection, exfiltration, secret-leak, and obfuscation signatures, redacting matched sections by default. Set NAB_YARA_ACTION=refuse to block the fetch outright (or NAB_YARA_BYPASS=1 as an audited emergency opt-out).

The net effect: hidden instructions become visible to you, not executed by your model — a strong reason to point your agent at nab fetch instead of a built-in web-fetch tool.

> Licensing: both guards are Enterprise Edition modules — free for personal and non-commercial use under [PolyForm Noncommercial 1.0.0](LICENSE-EE.md); commercial / business use requires a commercial license (see [COMMERCIAL.md](COMMERCIAL.md) and the [License](#license) section).

Installation

Homebrew (macOS, recommended)

brew tap MikkoParkkola/tap
brew install nab

Pre-built binary (no Rust toolchain required)

Most users want this path — these are ready-to-run binaries; nothing is compiled on your machine.

If you have cargo-binstall, it fetches the right pre-built binary automatically:

cargo binstall nab

Otherwise download directly from GitHub Releases. Both the nab CLI and the nab-mcp server ship for every platform below, alongside checksums-sha256.txt:

| Platform | CLI binary | MCP server binary | |----------|------------|-------------------| | macOS Apple Silicon | nab-aarch64-apple-darwin | nab-mcp-aarch64-apple-darwin | | macOS Intel | nab-x86_64-apple-darwin | nab-mcp-x86_64-apple-darwin | | Linux x8664 (glibc) | nab-x86_64-unknown-linux-gnu | nab-mcp-x86_64-unknown-linux-gnu | | Linux x8664 (static musl) | nab-x86_64-unknown-linux-musl | nab-mcp-x86_64-unknown-linux-musl | | Linux ARM64 (glibc) | nab-aarch64-unknown-linux-gnu | nab-mcp-aarch64-unknown-linux-gnu | | Linux ARM64 (static musl) | nab-aarch64-unknown-linux-musl | nab-mcp-aarch64-unknown-linux-musl | | Windows x64 | nab-x86_64-pc-windows-msvc.exe | nab-mcp-x86_64-pc-windows-msvc.exe |

Example install for macOS Apple Silicon (substitute the filename for your platform):

shasum -a 256 -c checksums-sha256.txt --ignore-missing
chmod +x nab-aarch64-apple-darwin
mv nab-aarch64-apple-darwin /usr/local/bin/nab
xattr -d com.apple.quarantine /usr/local/bin/nab 2>/dev/null || true

From crates.io (compiles from source)

Builds nab locally — requires the Rust toolchain (1.95 or newer) and takes a few minutes:

cargo install nab

From source

git clone https://github.com/MikkoParkkola/nab.git
cd nab
cargo install --path .

Avoiding duplicate installs

If you install nab through more than one channel (for example a Homebrew tap and cargo install), the copy that wins depends on PATH order. On many setups /opt/homebrew/bin comes before ~/.cargo/bin, so a Homebrew binary can shadow a newer cargo-installed one — and nab --version then reports the older version.

Run the built-in diagnostic to see every nab on your PATH, which one wins, and their versions:

nab doctor

If the binary on your PATH is the stale one, its doctor may predate this command; invoke the newer install by full path to diagnose, e.g. ~/.cargo/bin/nab doctor. To resolve, keep a single install channel (brew uninstall nab or cargo uninstall nab), or reorder PATH so the directory of the install you want comes first.

MCP Configuration

Add to your MCP client config (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "nab": {
      "command": "nab-mcp"
    }
  }
}

Or use the auto-installer:

nab mcp install                        # Claude Desktop (default)
nab mcp install --client claude-code   # Claude Code
nab mcp install --client cursor        # Cursor
nab mcp install --client windsurf      # Windsurf
nab mcp install --client codex         # OpenAI Codex CLI
nab mcp install --client vscode        # VS Code Copilot
nab mcp install --client zed           # Zed
nab mcp install --dry-run              # preview without writing

Also supported: gemini, amazon-q, lm-studio.

See [MCP integration](#mcp-integration) below for the full list of tools, capabilities, and HTTP transport.

Claude Code plugin

This repository includes a local Claude Code plugin in [plugin/](plugin/README.md). It bundles nab MCP auto-registration with the Claude Elite research, url-insight, wayback, ia, and oreilly skills.

claude --plugin-dir ./plugin

The plugin exposes the /nab workflow shape for fetch, authenticated Brave-cookie fetches, archive retrieval, and multi-source research. It keeps nab's auth-aware path front and center: nab fetch --cookies brave for existing browser sessions and nab fetch --1password for 1Password/TOTP flows.

Usage

Fetch

# Basic fetch — auto-detects browser, returns markdown
nab fetch https://example.com

# Use cookies from a specific browser
nab fetch https://github.com/notifications --cookies brave

# 1Password auto-login (TOTP/MFA supported)
nab fetch https://internal.company.com --1password

# Google Workspace (Docs, Sheets, Slides) with comments
nab fetch --cookies brave "https://docs.google.com/document/d/DOCID/edit"

# Output JSON with confidence scores
nab fetch https://example.com --format json

# Batch fetch with parallelism
nab fetch --batch urls.txt --parallel 8

# Explicit browser rendering for JS-heavy pages
NAB_BROWSER_CDP_WS=wss://... nab browser https://example.com
nab fetch https://example.com --render --browser-cdp-url wss://...

Common flags for fetch:

| Flag | Description | |------|-------------| | --cookies | auto, brave, chrome, firefox, safari, edge, none | | --1password / --op | 1Password credential lookup + auto-login | | --proxy | HTTP or SOCKS5 proxy | | --format | full (default), compact, json | | --raw-html | Skip markdown conversion | | --readability | Force readability extraction for generic HTML pages | | --max-output-tokens | Apply an output token envelope; returned markdown uses 80% for headroom | | --remote-fallback | Opt in to remote thin-content recovery via r.jina.ai; avoid for internal, authenticated, or sensitive URLs | | --render / --interactive | Opt in to configured CDP browser rendering for JS-heavy pages; requires NAB_BROWSER_CDP_WS or --browser-cdp-url | | --diff | Show what changed since the last fetch | | -X -d | HTTP method + body | | -o | Write body to file |

MCP fetch additionally supports focus, readability, max_tokens, and session parameters for query-focused extraction, readability extraction, structure-aware token budgets, and persistent encrypted cookie sessions.

Analyze

nab analyze transcribes audio and video files locally. The default backend on macOS arm64 is FluidAudio, which runs Parakeet TDT v3 on the Apple Neural Engine.

# Download the ASR model (~600 MB, one-time)
nab models fetch fluidaudio

# Transcribe a video
nab analyze interview.mp4

# Add speaker diarization (PyAnnote community-1)
nab analyze interview.mp4 --diarize

# Force a language hint (BCP-47)
nab analyze podcast.mp3 --language fi

# Word-level timestamps
nab analyze talk.mp4 --word-timestamps

# Active reading: nab uses MCP sampling to look up references mentioned in the audio
nab analyze interview.mp4 --active-reading

# Expose speaker embeddings for matching against hebb's voiceprint database
nab analyze interview.mp4 --diarize --include-embeddings

# Output JSON
nab analyze podcast.mp3 --format json

Real numbers from a 2 h 09 m English audio file (Karen Hao interview, MacBook Pro M-series):

| Metric | Value | |--------|-------| | Wall time | 59.6 s | | Realtime factor | 131x | | FluidAudio mean confidence | 97.18 % | | Audio extraction (ffmpeg) | ~650x realtime |

| Backend | Platform | Languages | Diarization | |---------|----------|-----------|-------------| | fluidaudio (default on macOS arm64) | macOS arm64 | 25 EU languages, +zh/ja/ko/vi via Qwen3-ASR (opt-in) | PyAnnote community-1 | | sherpa-onnx | Linux/x86, macOS, Windows | Parakeet ONNX, 25+ langs | sherpa-onnx pyannote-seg-3.0 | | whisper-rs | Universal fallback | whisper-large-v3-turbo, 99 langs | none |

Watch

nab watch turns any URL into a subscribable resource. MCP clients receive notifications/resources/updated when the content changes.

nab watch add https://news.ycombinator.com --interval 10m
nab watch add https://example.com/pricing --interval 1h --selector "table.pricing"
nab watch add https://api.openai.com/status --interval 5m --notify-on regression
nab watch list
nab watch logs 
nab watch remove 

Per-watch options:

| Flag | Default | Description | |------|---------|-------------| | --interval | 1h | Polling interval (5m, 1h, 24h) | | --selector | none | CSS selector to scope diff to one element | | --notify-on | any | any, regression, semantic | | --diff | semantic | text, semantic, dom |

The poller uses conditional GETs (If-None-Match, If-Modified-Since), so 304 responses cost effectively nothing. Watches with five consecutive failures auto-mute. Adaptive backoff applies on 429 and 503.

Models

nab models list                           # show installed model versions
nab models fetch fluidaudio               # download FluidAudio binary + Parakeet weights
nab models update fluidaudio              # check for upstream updates
nab models verify fluidaudio              # checksum + smoke test

Both whisper and sherpa-onnx ship as cross-platform fallbacks alongside the macOS-default fluidaudio backend.

MCP integration

nab-mcp is a native Rust MCP server. It runs over stdio (default) or Streamable HTTP. It is fully compliant with MCP protocol version 2025-11-25.

Quick setup (recommended)

nab mcp install                        # Claude Desktop (default)
nab mcp install --cl

…

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [MikkoParkkola](https://github.com/MikkoParkkola)
- **Source:** [MikkoParkkola/nab](https://github.com/MikkoParkkola/nab)
- **License:** MIT
- **Homepage:** https://crates.io/crates/nab

Install and usage instructions live in the source repository linked above.