Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Fabric MCP

by mpzardeversion 1.0.0i★ –iRuns on your computer
Registry nameio.github.mpzarde/fabric-mcp

Install

Overview

Description from the maker (original English)

MCP server for Fabric AI patterns

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: Other

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).
  • You fill in yourself: FABRIC_PATH, YTDLP_PATH

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "fabric": {
      "command": "npx",
      "args": [
        "-y",
        "@angrydad67/fabric-mcp-server"
      ],
      "env": {
        "FABRIC_PATH": "your-value",
        "YTDLP_PATH": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add fabric --env FABRIC_PATH=your-value --env YTDLP_PATH=your-value -- npx -y @angrydad67/fabric-mcp-server

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "fabric": {
      "command": "npx",
      "args": [
        "-y",
        "@angrydad67/fabric-mcp-server"
      ],
      "env": {
        "FABRIC_PATH": "your-value",
        "YTDLP_PATH": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "fabric": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@angrydad67/fabric-mcp-server"
      ],
      "env": {
        "FABRIC_PATH": "your-value",
        "YTDLP_PATH": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • FABRIC_PATH env
    Custom path to Fabric CLI (optional, uses PATH by default)
  • YTDLP_PATH env
    Custom path to yt-dlp CLI (optional, uses PATH by default)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

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 mpzarde, 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 Otheri

  • More stars than 0% of the other 18336 servers in this category
  • Published to the registry more recently than 2% of the other 18336 servers in this category
  • Basic checks equal to or better than 100% of the other 18336 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 Fabric MCP 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 (1.0.0) reached the registry 9 months ago.

Which apps can use it?

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

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, NexusWindows

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

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
Install

NexusWindows

by pironjulien

Windows computer use in the background: desktop apps driven without your mouse or keyboard.

Runs on your computerUpdated today
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.

Fabric MCP Server

Model Context Protocol (MCP) server for Fabric - Daniel Miessler's AI-powered content processing framework.

This MCP server allows Claude (via Claude Desktop or Warp CLI) to use Fabric's extensive collection of AI patterns for content analysis, summarization, learning, coding, security analysis, and more.

Quick Start

  1. Install Fabric (if not already installed):

See the official Fabric installation guide for detailed instructions.

  1. Install yt-dlp (optional, for YouTube transcripts):
   # macOS

brew install yt-dlp

Linux/Windows

pip install yt-dlp

  1. Download and Install:
  • Download fabric-mcp.mcpb from Releases
  • Double-click the file
  • Click "Install" in Claude Desktop
  • Restart Claude Desktop
  1. Try it: Ask Claude: "List all fabric patterns"

Features

  • 🚀 Direct CLI Integration: Uses Fabric CLI directly (no REST API server needed)
  • 🔧 19 Pre-configured Tools: Direct access to commonly-used Fabric patterns plus combined analysis tools
  • 🎯 Generic Pattern Runner: Run any Fabric pattern with run_fabric_pattern
  • 📺 YouTube Support: Fetch video transcripts directly (requires yt-dlp)
  • 🔍 Pattern Discovery: List all available patterns dynamically
  • 📁 File & URL Analysis: Process files and web content with Fabric patterns
  • 🏥 Health Check: Verify dependencies and configuration

Prerequisites

1. Install Fabric

If you don't have Fabric installed, follow the official Fabric installation guide.

2. Install yt-dlp (Optional)

Required only if you want to fetch YouTube transcripts:

# macOS

brew install yt-dlp

Linux

pip install yt-dlp

Or: sudo apt install yt-dlp (on Ubuntu/Debian)

Windows

pip install yt-dlp

3. Verify Installation
# Test Fabric

fabric --version fabric --listpatterns

Test yt-dlp (optional)

yt-dlp --version

Installation

Option 1: Download and Install (Recommended) 🎉

The easiest way to install:

  1. Download the latest fabric-mcp.mcpb from Releases
  2. Double-click the downloaded file
  3. Claude Desktop will open and prompt you to install
  4. Click Install
  5. Restart Claude Desktop
  6. Done!

The .mcpb file is a self-contained bundle that includes everything needed.

Option 2: Build from Source

If you want to build from source:

git clone https://github.com/mpzarde/fabric-mcp.git

cd fabric-mcp npm install npm run build

Then either:

  • Build the `.mcpb` bundle: ./build-mcpb.sh (creates fabric-mcp.mcpb you can install)
  • Configure manually: See Configuration section below for manual setup

Configuration

For Claude Desktop

Note: If you installed using the .mcpb bundle (Option 1), Claude Desktop configures this automatically. This section is only needed for manual builds.

Add to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: %APPDATA%/Claude/claude_desktop_config.json

{

"mcpServers": { "fabric": { "command": "node", "args": ["/absolute/path/to/fabric-mcp/dist/index.js"] } } }

Replace `/absolute/path/to/fabric-mcp/` with your actual project path.

Optional environment variables (if needed):

"env": {

"FABRIC_PATH": "/custom/path/to/fabric", "YTDLP_PATH": "/custom/path/to/yt-dlp" }

For Warp CLI

Note: Manual configuration is required for Warp. Build from source or extract the .mcpb bundle first.

Add to your Warp MCP configuration file:

macOS/Linux: ~/.warp/mcp_config.json

{

"mcpServers": { "fabric": { "command": "node", "args": ["/absolute/path/to/fabric-mcp/dist/index.js"] } } }

Replace `/absolute/path/to/fabric-mcp/` with your actual project path.

Optional environment variables (if needed):

"env": {

"FABRIC_PATH": "/custom/path/to/fabric", "YTDLP_PATH": "/custom/path/to/yt-dlp" }

Restart Claude/Warp

After configuration:

  • Claude Desktop: Restart the application
  • Warp: Restart the terminal or run warp mcp reload

Available Tools

Core Tools
  1. `health_check` - Check if Fabric, yt-dlp, and other dependencies are installed and configured
  2. `list_fabric_patterns` - List all available Fabric patterns
  3. `run_fabric_pattern` - Run any Fabric pattern with custom input
  4. `get_youtube_transcript` - Fetch transcript from YouTube video
Combined Analysis Tools

These tools streamline common workflows by fetching content and applying patterns in one step. Benefits:

  • ✅ No truncation: Complete content is passed directly to Fabric
  • ✅ More efficient: Single tool call instead of multiple
  • ✅ Better results: Fabric processes the full content without context window limits
  1. `analyze_youtube_video` - Fetch YouTube transcript and apply a pattern in one step
  2. `analyze_file` - Read a file and apply a pattern in one step
  3. `analyze_url` - Fetch URL content and apply a pattern in one step
Pre-configured Pattern Tools

These patterns are exposed as dedicated tools with the fabric_ prefix:

Content Analysis
  • fabric_extract_wisdom - Extract key insights and quotes from content
  • fabric_summarize - Create concise summaries
  • fabric_analyze_claims - Analyze and fact-check claims
  • fabric_analyze_paper - Analyze academic papers
Learning
  • fabric_create_quiz - Generate quiz questions
  • fabric_to_flashcards - Convert content to flashcards
Development
  • fabric_summarize_git_diff - Summarize git diffs for reviews
  • fabric_create_coding_project - Generate project structure from ideas
  • fabric_explain_code - Explain code in simple terms
Security & Operations
  • fabric_analyze_logs - Analyze log files
  • fabric_analyze_incident - Analyze security incidents
Writing
  • fabric_improve_writing - Improve writing quality

Usage Examples

With Claude Desktop

Extract wisdom from a YouTube video:

User: Can you extract the key insights from this video? 

https://www.youtube.com/watch?v=dQw4w9WgXcQ

Claude: [Uses get_youtube_transcript + fabric_extract_wisdom]

Summarize an article:

User: Summarize this article: [paste article text]

Claude: [Uses fabric_summarize]

Create flashcards from lecture notes:

User: Convert these lecture notes into flashcards: [paste notes]

Claude: [Uses fabric_to_flashcards]

Analyze a git diff:

User: Review this git diff and summarize the changes:

[paste git diff output]

Claude: [Uses fabric_summarize_git_diff]

Combined Analysis Tools

For efficiency, use the combined tools that fetch and analyze in one step:

User: Extract wisdom from this YouTube video:

https://www.youtube.com/watch?v=example

Claude: [Uses analyze_youtube_video with pattern='extract_wisdom']

User: Summarize this article: https://example.com/article

Claude: [Uses analyze_url with pattern='summarize']

User: Explain the code in /path/to/script.py

Claude: [Uses analyze_file with pattern='explain_code']

Chaining Patterns

Claude can chain multiple patterns together:

User: Get the transcript from this video, extract the wisdom, 

then create flashcards from it. https://www.youtube.com/watch?v=example

Claude: [1. Uses get_youtube_transcript] [2. Uses fabric_extract_wisdom on transcript] [3. Uses fabric_to_flashcards on extracted wisdom]

Use Cases

Based on Daniel Miessler's Fabric patterns:

Content Processing
  • YouTube video → extract wisdom / summarize
  • Article / blog post → summarize, analyze claims
  • Podcast transcript → extract wisdom, pull quotes
Writing & Development
  • Idea → essay (via create_coding_project or similar patterns)
  • Code diff → PR description (via summarize_git_diff)
  • Meeting notes → user stories (via run_fabric_pattern with agility_story)
Learning
  • Any content → flashcards (via to_flashcards)
  • Dense docs → glossary with analogies
  • Video/article → quiz (via create_quiz)
Security Analysis
  • Malware samples → analysis (via analyze_malware)
  • Log files → threat interpretation (via analyze_logs)
  • Security scans → rules (via run_fabric_pattern)

Troubleshooting

Check server health

Ask Claude: "Run a health check" - this will verify:

  • Fabric installation and version
  • Fabric configuration (API keys, patterns)
  • yt-dlp installation (for YouTube support)
  • Provide installation instructions if anything is missing
Common Issues
Fabric not found

Error: Failed to spawn fabric: ENOENT

Solutions:

  1. Install Fabric following the official installation guide
  2. Verify installation: which fabric and fabric --version
  3. If using a custom Fabric location, set FABRIC_PATH in your MCP config
Pattern not found

Error: Pattern not found: pattern_name

Solutions:

  1. Ask Claude to list all patterns: "List all fabric patterns"
  2. Update patterns: fabric --updatepatterns
  3. Check spelling - use underscores (e.g., extract_wisdom not extractWisdom)
YouTube transcripts not working

Error: Failed to fetch YouTube transcript

Solutions:

  1. Install yt-dlp: brew install yt-dlp (macOS) or pip install yt-dlp
  2. Verify: yt-dlp --version
  3. If using custom location, set YTDLP_PATH in your MCP config
MCP server not appearing in Claude

Solutions:

  1. Verify config file location:
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%/Claude/claude_desktop_config.json
  1. Check JSON syntax with a validator
  2. Ensure path to dist/index.js is absolute
  3. Restart Claude Desktop completely
  4. Check logs: ~/Library/Logs/Claude/mcp-server-fabric.log
Pattern execution timeout

Error: Fabric command timed out

Solutions:

  • Large patterns may take time (default: 5 minutes)
  • Check your Fabric API keys and quota
  • Try with a smaller input first

Development

Build
# Build TypeScript only

npm run build

Build complete .mcpb bundle

./build-mcpb.sh

Watch mode
npm run watch
Testing locally
# Build the project

npm run build

Test the MCP server

node dist/index.js

Server will run on stdio and wait for MCP protocol messages

Or use the health check to verify dependencies

echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"health_check","arguments":{}}}' | node dist/index.js

Architecture

┌─────────────────┐

│ Claude/Warp │ └────────┬────────┘ │ MCP Protocol (stdio) ▼ ┌─────────────────┐ │ MCP Server │ ← This project │ (Node.js) │ └────────┬────────┘ │ Direct CLI calls ▼ ┌─────────────────┐ │ Fabric CLI │ │ (fabric cmd) │ └────────┬────────┘ │ ▼ ┌─────────────────┐ │ AI Patterns │ │ OpenAI/etc. │ └─────────────────┘

The MCP server:

  1. Exposes Fabric patterns as MCP tools
  2. Calls Fabric CLI directly with pattern names and input
  3. Returns results back to Claude/Warp
  4. No REST API server needed - uses CLI interface

Resources

  • Fabric: https://github.com/danielmiessler/Fabric
  • yt-dlp: https://github.com/yt-dlp/yt-dlp
  • MCP Documentation: https://modelcontextprotocol.io
  • MCP SDK: https://github.com/modelcontextprotocol/typescript-sdk

License

MIT

Contributing

Contributions welcome! Please open an issue or PR.

Credits

  • Fabric by [Daniel Miessler](https://gith

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

Ask PopNx