<!-- faf: claude-faf-mcp | TypeScript | mcp-server | FAF MCP server for Claude — persistent project context, 13 Core tools (36 total) --> <!-- faf: doc=readme | canonical=project.faf | score=100 | family=FAF -->

claude-faf-mcp — 🧡 The Heartbeat 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.

🧡 v5.13.0 — 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 (36 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:

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](https://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 →](https://www.npmjs.com/package/faf-cli)

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

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, 36 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 36 (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

Validate & Score

Sync & Persist

Export & Interop

Read & Write

[Full tool reference →](https://github.com/Wolfe-Jam/claude-faf-mcp/blob/main/docs/mcp-tools.md)

🐘 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](https://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

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

Quality

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

[CI Dashboard →](https://github.com/Wolfe-Jam/claude-faf-mcp/actions/workflows/ci.yml)

Privacy

Everything runs locally. No data leaves your machine. No analytics, no telemetry, no tracking, no accounts. [Privacy policy →](./PRIVACY.md)

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

format | driven 🏎️⚡️ [wolfejam.dev](https://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](https://github.com/modelcontextprotocol/servers/pull/2759) · 2 IANA registrations: vnd.faf+yaml (Context) · vnd.fafm+yaml (Memory) · faf.one · npm

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