MCP Connector

Manage Project Context with FAF MCP

Give Claude persistent project context via the .faf format, auto-synced to CLAUDE.md and MEMORY.md across every session.

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Version 5.15.0
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Why it matters

Integrate Foundational AI-context Format (FAF) into your projects for persistent context management. This MCP server provides over 50 tools for AI readiness assessment, project analysis, and context optimization.

Outcomes

What it gets done

01

Create and manage project.faf files for LLM compatibility.

02

Assess and score your project's AI readiness.

03

Enhance and optimize project context files.

04

Parse, validate, and compress FAF files.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-claude-faf-mcp | bash

Capabilities

Tools your agent gets

faf_quick

Lightning-fast project.faf creation with average 3ms execution time

faf_enhance

Intelligent enhancement of FAF files with auto-detection capabilities

faf_read

Parse and validate FAF files for project context extraction

faf_write

Create or update FAF files with validation

faf_score

AI readiness scoring engine with level-based ranking

faf_compress

Intelligent size optimization for FAF project context files

Overview

claude-faf-mcp MCP Server

claude-faf-mcp gives Claude persistent project context through the .faf format, syncing it into CLAUDE.md and, optionally, MEMORY.md. It ships 13 core tools for creating, scoring, and syncing this context, with 35 available in total. Use it for projects spanning many sessions or team members, where you want Claude grounded in project intent from the first message. Skip it for one-off tasks with no recurring context to preserve.

What it does

claude-faf-mcp is an MCP server that gives Claude persistent, structured project context using the .faf file format - an IANA-registered format (application/vnd.faf+yaml) for capturing what a project is, who it's for, and why it exists. Instead of re-explaining your project at the start of every session, .faf stores the 3Ws (who, what, why) and, for full optimization, the 6Ws (adding where, when, how). The server exposes a Core set of 13 self-documenting MCP tools by default (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), with 35 tools available when FAF_TOOLS=all is set - covering creation/detection, validation/scoring, sync/persistence, and export/interop.

When to use - and when NOT to

Use this when working in Claude Code or Claude Desktop on a project you return to across many sessions, and you want the AI grounded in project intent (the human context code can't carry) rather than just file contents. It's particularly useful for teams: committing project.faf to the repo means every teammate's Claude - and a fresh git clone - starts already grounded. It is not needed for one-off, single-session tasks where there's no recurring context to preserve, and its AI-readiness scoring (Trophy 100% down to White 0%) is a self-assessment mechanism specific to the .faf format, not a general code-quality metric.

Inputs and outputs

Inputs are your project's existing files (language, framework, package manager, build tools are auto-detected) plus the human-only context you provide - the 3Ws/6Ws. Output is a project.faf file plus its syncs: faf_sync writes .faf into CLAUDE.md (bi-sync) and can also emit AGENTS.md, .cursorrules, GEMINI.md, and .github/copilot-instructions.md when the agents/cursor/gemini/copilot/all flag is used; faf_tri_sync additionally syncs to MEMORY.md for cross-session memory. faf_score returns an AI-readiness score (0-100%) with a breakdown, and faf_bench benchmarks grounding lift by comparing Claude's answers about the repo with and without .faf, emitting a verification receipt.

How to install

npm install -g claude-faf-mcp

Then add to claude_desktop_config.json:

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

Restart Claude Desktop, then type /faf to have Claude check, score, and sync the project, or state your 3Ws directly ("I'm building [what] for [who] because [why]"). For Claude Code, install the native SessionStart hook via faf_setup (previews changes first) so each session opens with a one-line context heartbeat.

Who it's for

Developers and teams using Claude Code or Claude Desktop across long-running projects who want consistent, machine-readable project context that travels with the repo - avoiding both context loss between sessions and drift between teammates. Everything runs locally with no telemetry or accounts. Licensed MIT.

Source README

claude-faf-mcp - The Instructions Edition

npm version
FAF Trophy 100%
IANA: vnd.faf+yamlIANA: vnd.fafm+yaml
DOI: Context paperDOI: Memory paper

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

Persistent Project Context with Memory, looped for you. One-click setup. 30 seconds. ๐Ÿ˜ Nelly Never Forgets.

FAF
Anthropic MCP
CI
NPM Downloads
License: MIT
Chat to FAFA live

FAF defines. MD instructs. AI codes.

๐Ÿ˜ tri-sync now free for all builders - .faf โ†” CLAUDE.md โ†” MEMORY.md in one command. Pro feature. Now free.

โšก 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.

๐Ÿงก 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 โœช 100% โ€” fresh ยท +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.

๐Ÿ† 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 โœช receipt showing the delta. Promoted to lead the Core tier (13 tools, 36 total). faf_go now bootstraps a cold repo (init โ†’ auto โ†’ 6Ws), and you can still just type faf to start. Proof, not pitch.

๐Ÿ† 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.

๐Ÿ† 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.

๐Ÿ† 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 + โœช parity receipt) and keeps it fresh. FAF don't lie, by construction.

๐Ÿ† 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 โœช heartbeat (faf: context โœช 100% โ€” 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 โœช 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 ยท 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 โ†’ 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 โ†’

Claude Desktop - click, copy, paste, install

Click - one-click .mcpb

โฌ‡ 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 โ†’ 3 answers โ†’ project.faf โ†’ AI reads it โ†’ every session โ†’ forever

project.faf  โ†โ”€โ”€ 8ms โ”€โ”€โ†’  CLAUDE.md     (bi-sync, free)
project.faf  โ†โ”€โ”€ 8ms โ”€โ”€โ†’  MEMORY.md     (tri-sync, Pro ๐Ÿ˜)

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 โœช 100% โ€” fresh ยท +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  โ†’  every teammate's Claude starts with the same context
git clone           โ†’  a new dev's Claude is grounded before they write a line
  • One source of truth. .faf โ†” CLAUDE.md stay in sync (bi-sync'd). Add MEMORY.md for cross-session memory (tri-sync ๐Ÿ˜).
  • 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 โ†’ 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
๐Ÿ† TROPHY 100% Gold Code - AI is optimized
โ˜… GOLD 99%+ Near-perfect context
โ—† SILVER 95%+ Excellent
โ—‡ BRONZE 85%+ Production ready
โ— GREEN 70%+ Solid foundation
โ— YELLOW 55%+ AI flipping coins
โ—‹ RED <55% AI working blind
โ™ก 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 ยท faf_auto ยท faf_go ยท faf_bench ยท faf_enhance ยท faf_score ยท faf_doctor ยท faf_sync ยท faf_context ยท faf_trust ยท faf_about ยท faf_etch ยท 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 โœช 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 โ†’ CLAUDE.md - agents/cursor/gemini/copilot/all also emit AGENTS.md / .cursorrules / GEMINI.md / copilot-instructions.md
faf_tri_sync Tri-sync .faf โ†” CLAUDE.md โ†” MEMORY.md - Pro feature, free for developers ๐Ÿ˜
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 โ†’


๐Ÿ˜ Nelly Never Forgets

bi-sync keeps .faf โ†” CLAUDE.md aligned.

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

bi-sync  = .faf โ†” CLAUDE.md              โ† always in sync
tri-sync = .faf โ†” CLAUDE.md โ†” MEMORY.md  โ† Nelly never forgets ๐Ÿ˜

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


The .FAF Position

Model        Context          Protocol
โ”€โ”€โ”€โ”€โ”€        โ”€โ”€โ”€โ”€โ”€โ”€โ”€          โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
Claude    โ†’   .faf        โ†’    MCP
Gemini    โ†’   .faf        โ†’    MCP
Codex     โ†’   .faf        โ†’    MCP
Any LLM   โ†’   .faf        โ†’    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 ยท 28 suites ยท 3 platforms (bun on ubuntu/macos/windows)

CI Dashboard โ†’


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}
}

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 ๐ŸŽ๏ธโšก๏ธ 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 ยท 2 IANA registrations: vnd.faf+yaml (Context) ยท vnd.fafm+yaml (Memory) ยท faf.one ยท npm


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

FAQ

Common questions

Discussion

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