Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
MCP server for Fabric AI patterns
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
FABRIC_PATH, YTDLP_PATHYou need
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-serverFill in the empty values before running it.
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.
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.
FABRIC_PATH envYTDLP_PATH envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account mpzarde, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 9 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, NexusWindows
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Windows computer use in the background: desktop apps driven without your mouse or keyboard.
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.
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.
See the official Fabric installation guide for detailed instructions.
# macOS
brew install yt-dlp
pip install yt-dlp
fabric-mcp.mcpb from Releasesrun_fabric_patternIf you don't have Fabric installed, follow the official Fabric installation guide.
Required only if you want to fetch YouTube transcripts:
# macOS
brew install yt-dlp
pip install yt-dlp
pip install yt-dlp
# Test Fabric
fabric --version fabric --listpatterns
yt-dlp --version
The easiest way to install:
fabric-mcp.mcpb from ReleasesThe .mcpb file is a self-contained bundle that includes everything needed.
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-mcpb.sh (creates fabric-mcp.mcpb you can install)Note: If you installed using the
.mcpbbundle (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" }
Note: Manual configuration is required for Warp. Build from source or extract the
.mcpbbundle 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" }
After configuration:
warp mcp reloadThese tools streamline common workflows by fetching content and applying patterns in one step. Benefits:
These patterns are exposed as dedicated tools with the fabric_ prefix:
fabric_extract_wisdom - Extract key insights and quotes from contentfabric_summarize - Create concise summariesfabric_analyze_claims - Analyze and fact-check claimsfabric_analyze_paper - Analyze academic papersfabric_create_quiz - Generate quiz questionsfabric_to_flashcards - Convert content to flashcardsfabric_summarize_git_diff - Summarize git diffs for reviewsfabric_create_coding_project - Generate project structure from ideasfabric_explain_code - Explain code in simple termsfabric_analyze_logs - Analyze log filesfabric_analyze_incident - Analyze security incidentsfabric_improve_writing - Improve writing qualityExtract 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]
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']
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]
Based on Daniel Miessler's Fabric patterns:
create_coding_project or similar patterns)summarize_git_diff)run_fabric_pattern with agility_story)to_flashcards)create_quiz)analyze_malware)analyze_logs)run_fabric_pattern)Ask Claude: "Run a health check" - this will verify:
Error: Failed to spawn fabric: ENOENT
Solutions:
which fabric and fabric --versionFABRIC_PATH in your MCP configError: Pattern not found: pattern_name
Solutions:
fabric --updatepatternsextract_wisdom not extractWisdom)Error: Failed to fetch YouTube transcript
Solutions:
brew install yt-dlp (macOS) or pip install yt-dlpyt-dlp --versionYTDLP_PATH in your MCP configSolutions:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%/Claude/claude_desktop_config.jsondist/index.js is absolute~/Library/Logs/Claude/mcp-server-fabric.logError: Fabric command timed out
Solutions:
# Build TypeScript only
npm run build
./build-mcpb.sh
npm run watch
# Build the project
npm run build
node dist/index.js
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"health_check","arguments":{}}}' | node dist/index.js
┌─────────────────┐
│ 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:
MIT
Contributions welcome! Please open an issue or PR.
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