claude-faf-mcp

Wolfe-Jam/claude-faf-mcp

3.4

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The claude-faf-mcp is an official MCP server for the Foundational AI-context Format (FAF), providing a standardized context layer for AI models using the MCP protocol.

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claude-faf-mcp

IANA-Registered Format for AI Context Β· application/vnd.faf+yaml

Official MCP server for FAF (Foundational AI-context Format) with 50+ tools - Persistent project context that integrates seamlessly with Claude Desktop workflows

NPM Downloads Discord Chrome Web Store Website Spec Version IANA Registered License: MIT


Understanding MCP - Our Mission

The .FAF Position in the MCP Ecosystem:

Model        Context          Protocol
─────        ───────          ────────
LLM      β†’   IANA Format β†’    Open Protocol
Claude   β†’   .faf        β†’    MCP
Gemini   β†’   .faf        β†’    MCP
Codex    β†’   .faf        β†’    MCP
Any LLM  β†’   .faf        β†’    MCP

.FAF is the foundational, universal base layer for any Model using the MCP Protocol.

.FAF provides the standardized Context that makes the Model Context Protocol work for everyone.


🏎️ v3.0.5 - 100% Standalone Achievement

What's New in v3.0.5

100% STANDALONE OPERATION - Zero CLI dependencies across all 50 MCP tools.

Historic Milestone
  • βœ… 50/50 MCP tools operational (100% standalone)
  • βœ… 14/14 bundled commands (zero CLI dependencies)
  • βœ… 16.2x average speedup over CLI versions
  • βœ… 19ms average execution across all bundled commands
New Bundled Commands
  • faf_quick - Lightning-fast project.faf creation (3ms avg)
  • faf_enhance - Intelligent enhancement with auto-detection + MCP-native questionnaire (63ms)
Mk3 Bundled Engine

Core FAF CLI compiler code bundled directly into MCP:

  • 16.2x faster (direct function calls vs process spawning)
  • 19ms average across all bundled commands
  • Fastest: 1ms (formats command)
  • Unmeasurable: 0ms (migrate command - too fast!)
  • Zero memory leaks with championship-grade performance
project.faf Standard

ONE filename for new projects:

  • New files use project.faf (visible, universal standard)
  • Legacy .faf still readable (with gentle migration suggestion)
  • Visible like package.json (no more hidden files for new projects!)
  • ONE standard going forward across all tools and platforms

πŸ’‘ Legacy .faf Support with Migration Path

v3.0.0 prioritizes project.faf but still reads legacy .faf files.

What happens with .faf files:

  • βœ… Reads your existing .faf files (no breakage!)
  • πŸ’‘ Shows migration suggestion (gentle reminder)
  • 🚫 Never creates new .faf files (always uses project.faf)

To migrate (optional):

# Run this in your project directory:
faf migrate

# Takes <1 second, renames .faf β†’ project.faf

New projects automatically use project.faf - visible, universal, like package.json.

Installation

# Install/upgrade to v3.0.5
npm install -g claude-faf-mcp

# Or via npx (always gets latest)
npx -y claude-faf-mcp

Claude Desktop config (no changes needed if already using MCP):

{
  "mcpServers": {
    "claude-faf-mcp": {
      "command": "npx",
      "args": ["-y", "claude-faf-mcp"]
    }
  }
}

Performance Metrics

  • Average execution: 19ms (championship grade βœ…)
  • Fastest command: 1ms (formats)
  • Unmeasurable: 0ms (migrate - too fast to measure!)
  • Speedup vs CLI: 16.2x average
  • Memory: Zero leaks with championship performance βœ…
  • WJTTC Certified: 14/14 bundled commands, 50/50 tools, 100% pass rate βœ…

Claude Skills BUILT-IN - 6000+ lines TS-strict code faf-expert is on-hand, 24/7 - your resident faf specialist and Master of 21 Core Tools and 30+ Advanced Tools, 51 in all


TL;DR

Problem: AI needs persistent project contextβ€”not just md docs or tools, but foundational infrastructure.

Solution: The .faf format is a structured, machine-readable context layer. This MCP server gives Claude 50+ tools to create, score, and improve your project's persistent context through format-driven architecture.

How it works: Get a score (0-100%) showing how well AI understands your project. Higher scores = AI more in-tune with your codebase. Use tools to improve your score and context quality. Your .faf context persists across sessions.

DROP or PASTE, Click & Go!

🎯 Got .faf? DROP or PASTE it πŸ“¦ Got project? DROP or PASTE README or package.json πŸ’¬ Starting fresh? Just ask

Install:

Via npm:

npm install -g claude-faf-mcp

Via Homebrew:

brew install wolfe-jam/faf/claude-faf-mcp

Configure: Add to claude_desktop_config.json:

{
  "mcpServers": {
    "claude-faf-mcp": {
      "command": "claude-faf-mcp"
    }
  }
}

Using Other AI Tools?

This MCP server is for Claude Desktop. If you also use Claude Code, Cursor, Windsurf, Gemini CLI, OpenAI Codex, Warp, or any terminal-based AI:

Get faf-cli for universal AI context:

npm install -g faf-cli
# or
brew install faf-cli

Same project.faf format (lives right next to package.json and README.md). Works with every AI tool. faf-cli on npm β†’

Website β€’ Discord β€’ GitHub β€’ Discussions


πŸ“Έ See It In Action

project.faf sits right between package.json and README.md - exactly where it belongs.

Visible. Discoverable. Universal.


Official Status

claude-faf-mcp is officially published in the Anthropic MCP Registry (PR #2759). This is the first and only persistent project context server in the official Anthropic ecosystem.

Registry listing: "MCP server for .faf format. The only persistent project context scoring engine in the Anthropic registry."

Published to official Anthropic MCP registry with validation by Anthropic engineering team. Current metrics: 4,700 total downloads with 598 downloads per week.

Major Milestones

  • Aug 8, 2025 - Format created, first official .faf file is generated
  • Sep 1, 2025 - Developer platform launch (fafdev.tools)
  • Sep 11, 2025 - First Google Chrome Web Store approval
  • Sep 16, 2025 - MCP Server v2.0.0 published to npm
  • Sep 24, 2025 - CLI v2.1.0 published to npm
  • Oct 17, 2025 - Official Anthropic MCP Registry merger (PR #2759)
  • Oct 29, 2025 - Second Google Chrome Web Store approval
  • Oct 31, 2025 - IANA Registration πŸ† (application/vnd.faf+yaml)

Quadruple Validation: IANA, Anthropic, Google (2x)


What's New in v2.8.0 - Tool Visibility System

v2.8.0 introduces intelligent tool filtering to reduce cognitive load.

New Features

21 Core Tools (Default) Essential workflow tools shown by default:

  • Workflow: faf, faf_auto, faf_init, faf_innit, faf_status
  • Quality: faf_score, faf_validate, faf_doctor, faf_audit
  • Intelligence: faf_formats, faf_stacks, faf_skills
  • Sync: faf_sync, faf_bi_sync, faf_update, faf_migrate
  • AI: faf_chat, faf_enhance
  • Help: faf_index, faf_faq, faf_about

30+ Advanced Tools (Opt-in) Expert-level tools available via environment variable:

  • Display variants: faf_display, faf_show, faf_check
  • Trust system: faf_trust, faf_trust_confidence, faf_trust_garage
  • File operations: faf_read, faf_write, faf_list, faf_exists
  • DNA tracking: faf_dna, faf_log, faf_auth, faf_recover
  • Utilities: faf_choose, faf_clear, faf_share, faf_credit

Enable Advanced Tools:

{
  "mcpServers": {
    "claude-faf-mcp": {
      "command": "claude-faf-mcp",
      "env": {
        "FAF_MCP_SHOW_ADVANCED": "true"
      }
    }
  }
}

New! Claude Code Skill The faf-expert skill is now available - your on-hand 24/7 FAF specialist:

  • Expert guidance on .faf files and project DNA
  • Tool Visibility System documentation
  • MCP server configuration help
  • AI-readiness scoring assistance

Performance

  • <10ms tool filtering (5x better than 50ms championship target)
  • 57 tests passing - All existing functionality preserved
  • Zero regressions - Complete validation
  • WJTTC Gold Certified - F1-inspired testing standards

Previous: v2.7.2 - IANA Registration

On October 31, 2025, IANA officially registered .faf as application/vnd.faf+yaml - making it an Internet-standard format alongside PDF, JSON, and XML

  • API standardization across platforms

This documentation update adds IANA information throughout the README to reflect this major infrastructure-level achievement.


What's New in v2.7.0 - The Visibility Revolution

v2.7.0 introduces project.faf as the new standard for every repository.

project.faf in file structure

package.json for AI.

Just like package.json tells npm what your project needs, project.faf tells AI what your project IS.

FilePurposeWho Reads It
package.jsonDependencies, scripts, metadatanpm, Node.js, developers
project.fafContext, architecture, purposeAI, Claude, Cursor, any AI tool

Same pattern. Same universality. Same necessity.

What changed:

  • New projects create project.faf (not hidden .faf)
  • Your existing .faf files work perfectly
  • Rename with faf migrate (CLI v3.1.0) for better visibility

Why it matters:

# Before (hidden like secrets)
ls -la
.env          # Hidden (secrets - should be hidden)
.faf          # Hidden (AI context - should be visible!)

# After (visible like package.json)
ls
package.json  # Visible (dependencies)
project.faf   # Visible (AI context)
.env          # Still hidden (secrets stay secret)

.env hides secrets. project.faf shares context.

.faf was hiding in the wrong category. project.faf fixes that.

You wouldn't skip package.json. Don't skip project.faf.

Coordinated with faf-cli v3.1.0 for seamless ecosystem integration.


What is FAF?

FAF (Foundational AI-context Format) is the IANA-registered format for persistent project context in AI development tools.

Official Media Type: application/vnd.faf+yaml Registration Date: October 31, 2025 IANA Status: Recognized Internet standard

Why IANA Registration Matters

  • Internet-Scale Legitimacy - Same recognition as PDF (application/pdf), JSON (application/json), XML (application/xml)
  • Universal Compatibility - Browsers, email clients, APIs handle .faf files properly
  • HTTP Standard Headers - Content-Type: application/vnd.faf+yaml is officially registered
  • Future-Proof - Format backed by Internet standards body

The .faf Advantage

Traditional approach:

# Manual context setup (5+ minutes)
1. Copy README
2. List files
3. Explain architecture
4. Share with AI

FAF approach:

# Automated context (< 1 second)
npx -y claude-faf-mcp
faf init
# Done - complete project DNA in .faf file

What is claude-faf-mcp?

An MCP server that brings the .faf format to Claude Desktop for persistent project context. The .faf format (Foundational AI-Context Format) is a structured, machine-readable context layer designed as foundational infrastructureβ€”not tools, not documentation, but format.

Format-Driven Architecture

Everything flows through structured format. The .faf file is your project's persistent context layer. It survives across sessions, tools, and AI systems without re-explanation. It works with any MCP client, CLI, workflow automation (n8n, Make, etc.), or AI assistant. It supports any language, framework, or project setup. Optimized for Claude Desktop while maintaining compatibility with any AI model or platform.

Format-driven means the architecture is built on data structure first, not tooling first. Your project context becomes machine-readable, persistent, and interoperable. This is foundational infrastructure for AI-context operations.

Key Features

  • IANA-Registered Format - Official Internet media type application/vnd.faf+yaml

    • Proper HTTP Content-Type headers
    • Browser recognition and handling
    • Email client support
    • API standardization across platforms
  • 50+ MCP Tools - Complete project context management

    • Project DNA generation and scoring
    • Bi-directional CLAUDE.md sync
    • Format validation and conversion
  • Podium Quality Scoring - 0-100% AI-readiness assessment

    • πŸ† Trophy (85%+), πŸ₯‡ Gold (70%+), πŸ₯ˆ Silver (55%+), πŸ₯‰ Bronze (40%+)
  • Official Anthropic Registry - PR #2759 merged

    • Listed in official MCP server catalog
    • 4,700 total downloads (598/week)
    • Production-tested and validated

Zero configuration required - works out of the box after installation. Operations average under 11 milliseconds. Synchronizes .faf files with CLAUDE.md automatically. Built with 100% TypeScript strict mode. All 57 tests passing with production readiness confirmed.


Scoring System

Track your project's AI-readiness with a tiered scoring system:

Trophy (100%) - Podium. Perfect AI and human balance. Gold (99%) - Gold standard. Silver (95-98%) - Excellence. Bronze (85-94%) - Production ready. Green (70-84%) - Good foundation. Yellow (55-69%) - Getting there. Red (0-54%) - Needs attention.

Live output in Claude Desktop shows your score with a progress bar, current tier, and next milestone guidance.


Quick Start

Install globally via npm:

npm install -g claude-faf-mcp

Or via Homebrew:

brew install wolfe-jam/faf/claude-faf-mcp

Add to Claude Desktop configuration. On macOS and Linux, edit ~/Library/Application Support/Claude/claude_desktop_config.json. On Windows, edit %APPDATA%\Claude\claude_desktop_config.json.

{
  "mcpServers": {
    "claude-faf-mcp": {
      "command": "claude-faf-mcp"
    }
  }
}

Restart Claude Desktop to load the server.


Scoring System Experience

This is what persistent project context looks like in action. When you run faf_auto, Claude scores your project's AI-readiness with a visual breakdown showing exactly where you stand and what to improve next.

FAF Scoring Dashboard

Live in Claude Desktop. Persistent across sessions. Your foundational context layer, measured and actionable.


Available Tools

Core Tools

faf_init - Initialize project context. faf_innit πŸ‡¬πŸ‡§ - It's a Brit thing! (works same as init). faf_auto - Auto-detect and populate context. faf_score - Calculate AI readiness. faf_status - Project health check.

Enhancement Tools

faf_enhance - Optimize scoring. faf_sync - Sync files. faf_bi_sync - Bidirectional synchronization.

File Operations

faf_read - Read files. faf_write - Write files. faf_list - List directories. faf_search - Search file content.

Skills Integration

faf_skills - List Claude Code skills from .faf file.

Full tool documentation available at https://faf.one/docs/tools.


Usage Example

DROP or PASTE, Click & Go!

  1. DROP or PASTE any project file into Claude Desktop
  2. Type: "Run faf_auto to analyze this project"
  3. Get instant context - Claude understands your codebase
  4. Access 50+ commands naturally in conversation

The .faf file persists across conversations - no need to re-explain your project each time.


Technical Specifications

Performance: Sub-11ms average operation time. TypeScript: 100% strict mode. Dependencies: 1 (MCP SDK only). Testing: 730 C.O.R.E empirical tests (part of 12,500+ FAF ecosystem validation). Build: Zero errors. Coverage: 4,400+ lines of code.


Development

Clone the repository:

git clone https://github.com/Wolfe-Jam/claude-faf-mcp.git
cd claude-faf-mcp

Install dependencies and build:

npm install
npm run build

Run tests:

npm test

Link locally:

npm link

Requirements

Node.js 18 or later. Claude Desktop (latest version). Operating system: macOS, Linux, or Windows.


Claude Code Skill Installation

NEW: Install the faf-expert skill for enhanced FAF support in Claude Code:

# Install from npm package
mkdir -p ~/.claude/skills/faf-expert
cp node_modules/claude-faf-mcp/skill/SKILL.md ~/.claude/skills/faf-expert/

# Or download directly
curl -o ~/.claude/skills/faf-expert/SKILL.md \
  https://cdn.jsdelivr.net/npm/claude-faf-mcp@latest/skill/SKILL.md

Restart Claude Code to activate. The skill provides:

  • Expert guidance on .faf files and project DNA
  • v2.8.0 Tool Visibility System documentation
  • MCP server configuration help
  • AI-readiness scoring assistance

The FAF Ecosystem

faf-cli (npm) - Command line tool for local context management. claude-faf-mcp - This MCP server for Claude Desktop integration. faf.one - Documentation and guides. Chrome Extension - Browser integration for context collection. faf-expert skill - Claude Code integration for FAF expertise.


Author

James Wolfe (Wolfe-Jam), creator of the .faf format. ORCID: 0009-0007-0801-3841.


License

MIT License. See LICENSE file for details.

Note: The .faf-Engine is proprietary and available under separate license.


Contributing

Contributions are welcome. Join community discussions at https://github.com/Wolfe-Jam/claude-faf-mcp/discussions or submit issues and pull requests on GitHub.