nab

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.

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 <url>	Fetch any URL as clean markdown. HTTP/3, browser cookie injection (Brave / Chrome / Firefox / Safari / Edge / Dia), 1Password auto-login, fingerprint spoofing, 11 site providers. MCP fetch also supports query-focused extraction and token budgets.
nab analyze <video|audio>	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 <url>	Monitor a URL and push notifications via subscribable MCP resources. RSS for the entire web. Conditional GETs, semantic diff, adaptive backoff.
nab models fetch <name>	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.

Installation

Homebrew (macOS, recommended)

brew tap MikkoParkkola/tap
brew install nab

From crates.io

cargo install nab

Requires Rust 1.93 or newer.

Pre-built binary

cargo binstall nab

Or download directly from GitHub Releases:

Platform	Binary
macOS Apple Silicon	nab-aarch64-apple-darwin
macOS Intel	nab-x86_64-apple-darwin
Linux x86_64	nab-x86_64-unknown-linux-gnu
Linux ARM64	nab-aarch64-unknown-linux-gnu
Windows x64	nab-x86_64-pc-windows-msvc.exe

From source

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

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 below for the full list of tools, capabilities, and HTTP transport.

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

Common flags for fetch:

Flag	Description
--cookies <browser>	auto, brave, chrome, firefox, safari, edge, none
--1password / --op	1Password credential lookup + auto-login
--proxy <url>	HTTP or SOCKS5 proxy
--format <fmt>	full (default), compact, json
--raw-html	Skip markdown conversion
--remote-fallback	Opt in to remote thin-content recovery via r.jina.ai; avoid for internal, authenticated, or sensitive URLs
--diff	Show what changed since the last fetch
-X <method> -d <data>	HTTP method + body
-o <path>	Write body to file

MCP fetch additionally supports focus, max_tokens, and session parameters for query-focused 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 <id>
nab watch remove <id>

Per-watch options:

Flag	Default	Description
--interval <duration>	1h	Polling interval (5m, 1h, 24h)
--selector <css>	none	CSS selector to scope diff to one element
--notify-on <kind>	any	any, regression, semantic
--diff <kind>	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 --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 what would change

Also supported: gemini, amazon-q, lm-studio. This auto-detects the nab-mcp binary path, backs up your existing config, and adds the nab entry. Restart your client after installing.

Manual setup

Add to your MCP client configuration (~/.config/claude/mcp.json or equivalent):

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

HTTP transport

nab mcp serve --http 127.0.0.1:8765
# or directly:
nab-mcp --http 127.0.0.1:8765

Bind to localhost by default. Origin checks and MCP-Protocol-Version header validation are enforced per spec.

MCP capabilities

Capability	Status
Tools	12 tools with structured output schemas, annotations, validation errors
Prompts	4 prompts (fetch-and-extract, multi-page-research, authenticated-fetch, match-speakers-with-hebb)
Resources	2 static + N dynamic watch resources, all subscribable
Logging	notifications/message with RFC 5424 levels
Sampling	nab calls back to the host LLM for active reading, focus extraction, form auto-fill
Roots	roots/list queried for workspace-scoped saves
Elicitation	Form mode + URL mode for OAuth/SSO
Argument completion	completion/complete for tool args
Server icons	Light + dark SVG
Transports	stdio + Streamable HTTP (resumable, session-scoped)

The 12 MCP tools:

Tool	Description
fetch	Fetch URL → markdown, with cookies, focus, token budget, session
fetch_batch	Parallel multi-URL fetch with task-augmented async execution
submit	Submit a form with CSRF + smart field extraction
login	1Password auto-login with TOTP support
auth_lookup	Look up 1Password credentials for a URL
fingerprint	Generate browser fingerprint profiles
validate	Run the validation test suite
benchmark	Time URL fetches with stats
analyze	Transcribe and diarize audio/video
watch_create	Create a URL watch and subscribe
watch_list / watch_remove	Manage watches

Site providers

nab detects URLs for 11 platforms and uses their APIs or structured data instead of scraping HTML.

Provider	URL pattern	Method
Twitter / X	x.com/*/status/*	FxTwitter API
Reddit	reddit.com/r/*/comments/*	JSON API
Hacker News	news.ycombinator.com/item?id=*	Firebase API
GitHub	github.com/*/*/issues/*, */pull/*	REST API
Google Workspace	Docs, Sheets, Slides	Export API + OOXML
YouTube	youtube.com/watch?v=*, youtu.be/*	oEmbed
Wikipedia	*.wikipedia.org/wiki/*	REST API
StackOverflow	stackoverflow.com/questions/*	API
Mastodon	*/users/*/statuses/*	ActivityPub
LinkedIn	linkedin.com/posts/*	oEmbed
Instagram	instagram.com/p/*, */reel/*	oEmbed

If no provider matches, nab falls back to standard HTML fetch + markdown conversion.

Architecture

nab is built around a small set of orthogonal subsystems: cmd/ (CLI), bin/mcp_server/ (MCP server), content/ (HTML / PDF / OCR pipeline), analyze/ (ASR + diarization + vision), watch/ (URL monitoring + subscriptions), auth/ (cookies + 1Password + WebAuthn), site/ (per-site providers), and the shared AcceleratedClient (HTTP/3 + connection pool + fingerprint store).

See:

• docs/ARCHITECTURE.md — full module map and data flow
• docs/sovereign-stack.md — how nab composes with hebb to form a local-first multimodal stack
• docs/getting-started.md — new user onboarding

Design notes

The docs/design/ directory tracks recent design proposals:

• analyze-v2.md — multilingual ASR + diarization + vision pipeline
• url-watch-resources.md — URL watch as MCP subscribable resources
• active-reading.md — active reading via MCP sampling
• mcp-spec-closure.md — closing the last MCP 2025-11-25 spec gaps

Companion tools

nab is half of a sovereign multimodal stack. The other half is hebb, a neuroscience-inspired memory MCP server. Composition examples:

• nab analyze --diarize --include-embeddings → hebb voice_match → speakers labeled with names
• nab fetch URL → hebb kv_set → personal sovereign web memory
• nab watch add URL → hebb kv_set (on update) → time-series of changes to any web page

See docs/sovereign-stack.md for the full composition story.

Configuration

nab requires no configuration files. It uses smart defaults: auto-detected browser cookies, randomized fingerprints, and markdown output.

Persistent state lives in ~/.nab/:

Path	Purpose
~/.nab/snapshots/	Content snapshots for --diff change detection
~/.nab/sessions/	AES-256-GCM encrypted named-session jars (non-Windows)
~/.nab/session-key	Locally generated master key for session encryption (non-Windows)
~/.nab/fingerprint_versions.json	Cached browser versions (auto-updates every 14 days)
~/.local/share/nab/watches/	URL watch state
~/.local/share/nab/models/	Installed inference model binaries

Optional plugin configuration at ~/.config/nab/plugins.toml. See docs/getting-started.md for plugin examples.

Environment variables

Variable	Purpose
HTTPS_PROXY / https_proxy	HTTPS proxy URL
HTTP_PROXY / http_proxy	HTTP proxy URL
ALL_PROXY / all_proxy	Proxy for all protocols
RUST_LOG	Logging level (e.g., nab=debug)
PUSHOVER_USER / PUSHOVER_TOKEN	Pushover notifications for MFA
TELEGRAM_BOT_TOKEN / TELEGRAM_CHAT_ID	Telegram notifications for MFA

Library usage

use nab::AcceleratedClient;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let client = AcceleratedClient::new()?;
    let html = client.fetch_text("https://example.com").await?;
    println!("Fetched {} bytes", html.len());
    Ok(())
}

Requirements

• Rust 1.93+ for building from source
• ffmpeg for analyze and stream commands: brew install ffmpeg
• 1Password CLI (optional, for credential integration): see 1Password docs

Contributing

See CONTRIBUTING.md for development setup, code style guidelines, testing instructions, and pull request process.

Responsible use

This tool includes browser cookie extraction and fingerprint spoofing capabilities. They are intended for legitimate use cases — accessing your own authenticated content, automated testing, sites where you have authorization. Use responsibly.

Troubleshooting

MCP server not connecting? Run nab-mcp directly in your terminal to see errors. Verify the binary exists with which nab-mcp. If installed via cargo install nab, both nab and nab-mcp should be on your $PATH.

Cookie extraction failing? Grant Full Disk Access to your terminal in System Settings > Privacy & Security > Full Disk Access (macOS). Browser cookies are stored in protected directories. Use --cookies brave to target a specific browser.

ASR model not found? Run nab models fetch fluidaudio to download the model (~542 MB). The model directory is ~/.nab/models/. Use nab models list to see what's installed.

Fetch returning HTML instead of markdown? Some sites block automated access. Try nab fetch URL --cookies brave to use your browser session, or nab fetch URL --1password for sites that need login.

"too many open files" on watch? Increase your ulimit: ulimit -n 4096. The default macOS limit (256) is too low for many concurrent watches.

Ecosystem

nab is part of a suite of MCP tools:

Tool	Description
mcp-gateway	Universal MCP gateway — compact 12-15 tool surface replaces 100+ registrations
trvl	AI travel agent — 36 MCP tools for flights, hotels, ground transport
nab	Web content extraction — fetch any URL with cookies + anti-bot bypass
axterminator	macOS GUI automation — 34 MCP tools via Accessibility API

License

nab is dual-licensed as of v0.9.0:

Scope	License	File
Core fetch / analyze / watch / MCP server / public web fetching	MIT	LICENSE
Designated Enterprise Edition modules (authenticated reach + anti-bot)	PolyForm Noncommercial 1.0.0	LICENSE-EE.md

EE-designated paths (every file carries // SPDX-License-Identifier: PolyForm-Noncommercial-1.0.0):

• src/auth/ — 1Password, WebAuthn, and browser-cookie injection (premium authenticated reach)
• src/fingerprint/ — browser fingerprint spoofing (anti-bot evasion)
• src/waf/ — WAF challenge handling
• src/site/ — per-site provider integrations (proprietary domain knowledge)
• src/security/ — Secure Ingestion guard for stripping machine-targeted HTML directives and hidden metadata

What this means in practice:

• Free for noncommercial use, modification, redistribution.
• Commercial use of EE modules requires a separate commercial license — contact mikko.parkkola@iki.fi.
• All releases prior to v0.9.0 remain entirely MIT and stay MIT forever.