Claude-FAF-MCP Server

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Dokumentasi

claude-faf-mcp — The Instructions Edition

Home: faf.one/mcp Live demo: claude.faf.one

Persistent Project Context with Memory, looped for you. One-click setup. 30 seconds. 🐘 Nelly Never Forgets.

FAF defines. MD instructs. AI codes.

🐘 tri-sync now free for all builders — .faf ↔ CLAUDE.md ↔ MEMORY.md in one command. Pro feature. Now free.

⚡ New: /faf prompt — type /faf in Claude Desktop. It checks your project, scores it, drives it to 100%, and syncs. Relentlessly. One command.

v5.15.0 — The Instructions Edition. CFM writes the file Copilot reads — done right. .github/copilot-instructions.md is now genuine, distinct Copilot instructions: a prose overview, a ## Build & run command section, and "every request" framing — not the AGENTS.md content reused. The file Copilot actually reads, done to GitHub's spec.

v5.14.1 — The Copilot Edition. FAF now writes the file GitHub Copilot reads — from inside Claude. The Core faf_sync gains a copilot flag (all includes it), syncing .github/copilot-instructions.md — Copilot's widest-surface instruction file, read by default across web chat, code review, VS Code, JetBrains, the CLI, and the coding agent — straight from your scored .faf. faf_sync now emits every format (agents/cursor/gemini/copilot/all) from the default surface; the redundant faf_bi_sync is retired. Non-destructive, idempotent.

🧡 v5.13.0 — The Heartbeat Edition. Persistent Project Context with Memory, looped for you. Every Claude Code session now opens with a one-line heartbeat that carries the intent the code can't: faf: context ✪ 100% — fresh · +7 intent the code can't carry. The +N is the goal and 6Ws only you can give or confirm — so Claude starts each session grounded in what your project means, not just what it contains.

🏆 v5.12.0 — The Proof Edition. faf_bench proves FAF's grounding lift in-session — it asks Claude about your repo cold (no context) and with the .faf, grades mechanically (no judge), and emits a ✪ receipt showing the delta. Promoted to lead the Core tier (13 tools, 36 total). faf_go now bootstraps a cold repo (init → auto → 6Ws), and you can still just type faf to start. Proof, not pitch.

🏆 v5.11.0 — The Distilled Edition. claude-faf-mcp, distilled — a curated Core of 12 self-documenting tools, with the interview, README extractor, and server-card all composed from faf-cli's single source (no forks), and faf_go's new Table-of-8 where your goal seeds the 6Ws. Fewer tools, nothing forked, nothing guessed.

🏆 v5.10.0 — The Dart Edition. claude-faf-mcp now reads Dart & Flutter — it knows a Flutter app from a pure-Dart CLI. Detection by composition: because CFM composes faf-cli's Turbo-Cat (The Sourced Edition), faf-cli 6.13.0's content-aware, pubspec-driven Dart classifier arrives by construction — no forked parser, no drift. 35 tools, npm audit clean.

🏆 v5.9.0 — The Sourced Edition. Every answer comes from one source. faf_go and Turbo-Cat detection now compose faf-cli's single-source engines instead of carrying their own copies — fills come from real evidence or stay honestly empty, nothing guessed. The legacy guessing extractor is gone; the /faf prompt drives to a verified 100% (faf_trust + ✪ parity receipt) and keeps it fresh. FAF don't lie, by construction.

🏆 v5.8.0 — The Trust Edition. Claude Code-native context that just works. A native SessionStart hook opens every session with fresh context and a one-line ✪ heartbeat (faf: context ✪ 100% — fresh); tool output is quiet (no emoji, parseable) and typed (structuredContent everywhere); every score carries a deterministic parity hash any engine reproduces, sealed in a self-verifying ✪ receipt. Installed explicitly via faf_setup — preview first, your settings preserved. Built on the Canonical foundation: path-confined file access, edge-direct remote, 35 tools.

13 Core MCP tools (35 with FAF_TOOLS=all). IANA-registered formats (application/vnd.faf+yaml · application/vnd.fafm+yaml). 1,716 test executions per push.

The 3Ws — 3 Answers. That's It.

Every great product started with 3 answers to the 3Ws — Who, What, Why:

	WHO is it for?	WHAT does it do?	WHY build it?
Uber	People who need a ride	Tap a button, car arrives	Taxis were broken
Airbnb	Travelers who can't afford hotels	Stay in someone's spare room	Millions of empty rooms exist
Slack	Teams drowning in email	Organized group messaging	Decisions buried in threads
Venmo	Friends splitting bills	Send money instantly	Someone always forgets to pay back

Same pattern. Every product that works starts here. .faf captures it:

human_context:
  who: "people who need a ride across town"
  what: "tap a button, car arrives in minutes"
  why: "taxis are slow, expensive, and hard to find"

30 seconds. Claude builds your project.faf from this. Every session after, AI starts smart.

The 6Ws — For Optimized AI

3Ws gets you started. For fully optimized AI, complete the set — Where, When, How:

  where: "mobile app, iOS and Android"    # where does it live?
  when: "launch in 3 months"              # when is it shipping?
  how: "GPS matching, real-time pricing"  # how does it work?

3Ws initiates the project with AI. 6Ws optimizes AI to 100%. Same YAML, same file. More examples → faf.one/ideas

Quick Start

faf-cli — universal (any AI)

npx faf-cli auto

Same .faf, every surface — Claude, Gemini, Grok, Cursor. faf-cli on npm →

Claude Desktop — click, copy, paste, install

Click — one-click .mcpb

⬇ Download claude-faf-mcp-5.13.0.mcpb

Double-click. Zero-Config — no terminal, no JSON config. 13 Core tools live in 10 seconds.

Copy — paste-prompt to Claude

Install the FAF MCP server: npm install -g claude-faf-mcp, then add this to my claude_desktop_config.json: {"mcpServers": {"faf": {"command": "bunx", "args": ["claude-faf-mcp"]}}} and restart Claude Desktop.

Paste — claude_desktop_config.json

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

Install — manual npm

npm install -g claude-faf-mcp

Restart Claude Desktop.

Then

Type /faf — Claude checks your project, scores it, drives it to 100%, and syncs. Done.

Or tell Claude your 3Ws: "I'm building [what] for [who] because [why]"

How It Works

You → 3 answers → project.faf → AI reads it → every session → forever

project.faf  ←── 8ms ──→  CLAUDE.md     (bi-sync, free)
project.faf  ←── 8ms ──→  MEMORY.md     (tri-sync, Pro 🐘)

Claude does the rest. Zero-effort, right first time, fast, accurate, done. Language, framework, package manager, build tools — all auto-detected from your existing files. The human context is the part only you can give.

For Claude Code teams

.faf lives in the repo. Your context travels with the code — committed, versioned, done.

Every session starts grounded. Install the native SessionStart hook once (faf_setup — preview first, your settings preserved). After that, every Claude Code session opens with a one-line heartbeat instead of a blank slate:

faf: context ✪ 100% — fresh · +7 intent the code can't carry

That line is the relay: Claude already knows your stack and your score — and the +N is the intent the code can't carry: the goal and 6Ws only you can give or confirm. No re-explaining "what this project is" at the top of every session.

It scales to the team by construction:

commit project.faf  →  every teammate's Claude starts with the same context
git clone           →  a new dev's Claude is grounded before they write a line

One source of truth. .faf ↔ CLAUDE.md stay in sync (bi-sync'd). Add MEMORY.md for cross-session memory (tri-sync 🐘).
No drift. The score is deterministic — same .faf, same number, on every machine and in CI. A teammate can't be accidentally less grounded than you.
Local and private. Nothing leaves the machine — no accounts, no telemetry. The context is yours; it just rides in the repo.

Onboarding becomes git clone → grounded. The context a new teammate would normally pick up by asking around is already in the repo, machine-readable, from the first clone.

Scoring: From Blind to Optimized

Tier	Score	What it means
🏆 TROPHY	100%	Gold Code — AI is optimized
★ GOLD	99%+	Near-perfect context
◆ SILVER	95%+	Excellent
◇ BRONZE	85%+	Production ready
● GREEN	70%+	Solid foundation
● YELLOW	55%+	AI flipping coins
○ RED	<55%	AI working blind
♡ WHITE	0%	No context at all

At 55%, AI guesses half the time. At 100%, AI knows your project. Same compiler as faf-cli — same score everywhere.

MCP Tools — 13 Core, 35 with `FAF_TOOLS=all`

By default claude-faf-mcp advertises a distilled Core of 13 — the lifecycle tools you reach for, each self-documenting. Set FAF_TOOLS=all to expose all 35 (Extended tools stay callable by name regardless). Core 13: faf_init · faf_auto · faf_go · faf_bench · faf_enhance · faf_score · faf_doctor · faf_sync · faf_context · faf_trust · faf_about · faf_etch · faf_recall.

All tools run standalone — zero CLI dependencies, 19ms average execution.

Create & Detect

Tool	Purpose
`faf_init`	Initialize project DNA
`faf_auto`	Auto-detect stack and populate context
`faf_quick`	Lightning-fast creation (3ms)
`faf_readme`	Extract context from README (+25-35% boost)
`faf_formats`	Discover all formats in your project
`faf_git`	Extract context from any GitHub repo URL
`faf_human_add`	Add human context (the 6Ws)

Validate & Score

Tool	Purpose
`faf_score`	AI-readiness score (0-100%) with breakdown
`faf_bench`	Benchmark AI grounding — cold vs .faf, with a `✪` receipt
`faf_check`	Validate .faf structure
`faf_doctor`	Diagnose and fix common issues
`faf_go`	Guided interview to Gold Code

Sync & Persist

Tool	Purpose
`faf_sync`	Sync .faf → CLAUDE.md — `agents`/`cursor`/`gemini`/`copilot`/`all` also emit AGENTS.md / .cursorrules / GEMINI.md / copilot-instructions.md
`faf_tri_sync`	Tri-sync .faf ↔ CLAUDE.md ↔ MEMORY.md — Pro feature, free for developers 🐘
`faf_enhance`	Intelligent enhancement

Export & Interop

Tool	Purpose
`faf_agents`	Import/export AGENTS.md (OpenAI Codex)
`faf_cursor`	Import/export .cursorrules (Cursor IDE)
`faf_gemini`	Import/export GEMINI.md (Google Gemini)
`faf_conductor`	Import/export Conductor directory

Read & Write

Tool	Purpose
`faf_read`	Read any file
`faf_write`	Write any file
`faf_status`	Project status overview
`faf_debug`	Environment inspection
`faf_about`	What is .faf?

Full tool reference →

🐘 Nelly Never Forgets

bi-sync keeps .faf ↔ CLAUDE.md aligned.

tri-sync adds MEMORY.md — your AI remembers your project across every session.

bi-sync  = .faf ↔ CLAUDE.md              ← always in sync
tri-sync = .faf ↔ CLAUDE.md ↔ MEMORY.md  ← Nelly never forgets 🐘

Pro feature, free for developers. Teams & Enterprise: faf.one/pro (plans)

The .FAF Position

Model        Context          Protocol
─────        ───────          ────────
Claude    →   .faf        →    MCP
Gemini    →   .faf        →    MCP
Codex     →   .faf        →    MCP
Any LLM   →   .faf        →    MCP

IANA-registered (application/vnd.faf+yaml). Works with any AI. Define once, use everywhere.

Ecosystem

Package	Platform	Registry
claude-faf-mcp (this)	Claude	npm
faf-cli	Universal CLI	npm + Homebrew
gemini-faf-mcp	Google Gemini	PyPI
grok-faf-mcp	xAI Grok	npm
rust-faf-mcp	Rust	crates.io
faf-wasm	Browser/Edge	npm
Chrome Extension	Browser	Chrome Web Store

Same project.faf. Same scoring. Same result. Different execution layer.

Quality

572 tests · 28 suites · 3 platforms (bun on ubuntu/macos/windows)

CI Dashboard →

Privacy

Everything runs locally. No data leaves your machine. No analytics, no telemetry, no tracking, no accounts. Privacy policy →

If claude-faf-mcp has been useful, consider starring the repo — it helps others find it.

Citation

If you use claude-faf-mcp or the .faf / .fafm formats in research or production, please cite the format papers:

Wolfe, J. (2025). Format-Driven AI Context Architecture: The .faf Standard for Persistent Project Understanding. Zenodo. https://doi.org/10.5281/zenodo.18251362

Wolfe, J. (2026). Permanent Memory and Instant Recall: The .fafm Standard for Multi-Profile AI Agent Memory. Zenodo. https://doi.org/10.5281/zenodo.20348942

BibTeX

@article{wolfe2025faf,
  title     = {Format-Driven AI Context Architecture: The .faf Standard for Persistent Project Understanding},
  author    = {Wolfe, James},
  year      = {2025},
  month     = {nov},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.18251362},
  url       = {https://doi.org/10.5281/zenodo.18251362}
}

@article{wolfe2026fafm,
  title     = {Permanent Memory and Instant Recall: The .fafm Standard for Multi-Profile AI Agent Memory},
  author    = {Wolfe, James},
  year      = {2026},
  month     = {may},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.20348942},
  url       = {https://doi.org/10.5281/zenodo.20348942}
}

License

MIT — Free and open source

FAF Family


faf-cli	`npx faf-cli init` — create .faf for any project
claude-faf-mcp	MCP server for Claude Desktop
gemini-faf-mcp	MCP server for Gemini CLI
grok-faf-mcp	MCP server for Grok
faf-mcp	MCP server for Cursor, Windsurf, Cline, VS Code
rust-faf-mcp	MCP server in Rust
faf-skills	17 Claude Code skills
faf.one	Blog, downloads, docs
IANA: vnd.faf+yaml	Context format (2025-10-30)
IANA: vnd.fafm+yaml	Memory format (2026-05-13)

format | driven 🏎️⚡️ wolfejam.dev

Get the CLI

faf-cli — The original AI-Context CLI. A must-have for every builder.

npx faf-cli auto

Anthropic MCP #2759 · 2 IANA registrations: vnd.faf+yaml (Context) · vnd.fafm+yaml (Memory) · faf.one · npm

Zero-Config. Context that's just there — every session.