rust-faf-mcp

MCP serverDev tools

Lets your agent save and reuse persistent notes about a software project between sessions.

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About this server

Persistent project context, Rust-native MCP server. IANA-registered .faf format.

Getting started

  1. Save this item in Your setup as a reference.
  2. Read the source or reference documentation for its setup requirements. Saving it here does not connect it to your AI.
  3. Check this page for availability before trying to install it through Ahel.

From the project's README

As published by wolfe-jam/rust-faf-mcp in README.md.

Persistent Project Context for Rust MCP clients. Native. Fast. cargo install

The Table-of-8 Edition (v0.7.1) — one.faf/rust-faf-mcp · rmcp 3.0.1 (MCP Tier 1 foundation) · faf-rust-sdk 3.1 (the same always-33 kernel faf-wasm-sdk uses) · solid cargo-native Rust MCP for Rust devs

v0.7.1 — Pin the install. PATH rust-faf-mcp is not the pin. See CHANGELOG.

FAF defines. MD instructs. AI codes.

Stop re-explaining your project to every AI session. One .faf file holds your persistent project context. Every AI reads it once and knows what you're building.

Rust-native MCP (Model Context Protocol) server for FAF — structured AI project context in YAML (application/vnd.faf+yaml). Single binary, stdio transport, 4.3 MB stripped. Built on rmcp and faf-rust-sdk.

Quickstart

# Rust toolchain (install):
cargo install rust-faf-mcp --version 0.7.1

# No Rust (try — downloads GH Release binary for darwin/linux):
npx --yes rust-faf-mcp@0.7.1

Point an MCP client at the pin. A bare rust-faf-mcp on PATH may be an old Homebrew binary.

# Claude Code
claude mcp add faf -- npx --yes rust-faf-mcp@0.7.1
// WARP / Cursor / Zed / Claude Desktop — any stdio MCP client
{
  "mcpServers": {
    "faf": {
      "command": "npx",
      "args": ["--yes", "rust-faf-mcp@0.7.1"]
    }
  }
}

After cargo install rust-faf-mcp --version 0.7.1, "command": "rust-faf-mcp" is the install. Until you have proven that binary, use the npx pin.

No flags, no config files, no network listener. Pure stdio JSON-RPC.

Or via Homebrew (macOS, pre-built). If you already have it, upgrade — an old keg can sit on PATH as rust-faf-mcp:

brew update
brew install Wolfe-Jam/faf/rust-faf-mcp
# already installed:
brew upgrade Wolfe-Jam/faf/rust-faf-mcp

One command, done forever

faf_auto runs setup if project.faf is missing (tree detection writes mechanical facts), then syncs CLAUDE.md. It does not rewrite an existing file. Confirm setup (sweeps) lists what setup occupied — walk it; not a second write-gate. Empty human slots stay empty until you state them.

faf_auto complete
━━━━━━━━━━━━━━━━━
Score: 0% → 42% (+42) ● GREEN
Steps:
  1. Setup — created project.faf
  2. Created CLAUDE.md

Path: /home/user/my-project

Confirm setup (sweeps)
Walk these. Detection is already a fact. Not a second write-gate.
  project.name           my-api
  project.main_language  Rust
  stack.backend          Rust

What it produces:

# project.faf — your project, machine-readable
faf_version: "3.3"
project:
  name: my-api
  goal: REST API for user management
  main_language: Rust
  version: "0.1.0"
  license: MIT
instant_context:
  what_building: REST API for user management
  tech_stack: Rust 2024
  key_files:
    - Cargo.toml
    - src/main.rs
    - README.md
  commands:
    build: cargo build
    test: cargo test
stack:
  backend: Rust
  build: cargo

Every AI agent reads this once and knows exactly what you're building. No 20-minute onboarding. No wrong assumptions.

Tools

Create & Detect

ToolWhat it does
faf_autoSetup if missing, sync CLAUDE.md, score — Confirm setup (sweeps); does not invent 6Ws
faf_initSetup: first write from the tree. Refuses if the file exists. Confirm setup (sweeps). 6Ws stay empty
faf_goTable-of-8 + Confirm setup (sweeps). 6Ws score after ☑. Below 100: add Human Context. After 100: courtesy check every 30 days (90 max)
faf_gitGenerate project.faf from any GitHub repo URL — no clone needed
faf_discoverWalk up the directory tree to find the nearest project.faf

Score & Validate

ToolWhat it does
faf_scoreScore AI-readiness 0-100% with field-level breakdown
faf_syncSync project.faf → CLAUDE.md (preserves existing content)
faf_agentsGenerate AGENTS.md from project.faf (non-destructive, preserves hand-written content)

Optimize

ToolWhat it does
faf_readParse and display project.faf contents
faf_compressCompress .faf for token-limited contexts (minimal / standard / full)
faf_tokensEstimate token count at each compression level

faf_init will not overwrite an existing file. Setup occupies mechanical facts; Confirm setup (sweeps) is the walk. Empty human slots stay empty until faf_go.

Architecture

src/
├── main.rs      # ~20 lines — tokio entry, rmcp stdio transport
├── server.rs    # FafServer: #[tool_router], ServerHandler, resources
└── tools.rs     # Business logic — tools as pure functions returning Value
  • Runtime: tokio single-threaded (current_thread)
  • HTTP: reqwest async (only used by faf_git for GitHub API)
  • SDK: faf-rust-sdk 3.1 (Cargo pin — the facade over faf-kernel/faf-fafb in faf-rust; score() for the real Mk4 number, validate() for structural checks only)
  • Server: rmcp 3.0.1 with #[tool_router] / #[tool_handler] — JSON-RPC, schema generation, stdio transport (Tier-1 assessed SDK cut)

Tools return serde_json::Value. The server adapts them to Result<String, String> for rmcp's IntoCallToolResult.

Testing

171 tests (136 integration + 35 unit):

cargo test    # runs all 171

# Full ship bar (same gates as GitHub CI — run before push)
bash scripts/ci.sh
# Optional: block push on red CI twin
bash scripts/install-hooks.sh
FileTestsCoverage
mcp_protocol.rs9Init handshake, tools/list, resources, schema validation, ID preservation
tools_functional.rs31Tools — happy path, error paths, language detection, faf_go
tier1_security.rs12Path traversal, null bytes, shell injection, oversized input, malformed JSON
tier2_engine.rs36Corrupt YAML, sync replacement, pipelines, dual manifests, legacy filenames, direct paths
tier3_edge_cases.rs10Unicode, CJK, score boundaries, unknown fields, GitHub URL parsing
tier4_aero.rs22Manifest structure, version sync, server.json, context block, manifest-server cross-validation
wjttc_setup.rs16Setup / Confirm setup (sweeps) — BRAKE · ENGINE · AERO · TYRE · PIT
src unit35setup sweep, skills digest, agents::, inject::, intent, app-type

Tests spawn the compiled binary as a subprocess and communicate via stdin/stdout JSON-RPC — true integration tests against the real server.

FAF Ecosystem

One format, every AI platform.

PackagePlatformRegistry
rust-faf-mcpRustcrates.io
claude-faf-mcpAnthropicnpm + MCP #2759
gemini-faf-mcpGooglePyPI
grok-faf-mcpxAInpm
faf-cliUniversalnpm

Build from source

git clone https://github.com/Wolfe-Jam/rust-faf-mcp
cd rust-faf-mcp
cargo build --release
# Binary at target/release/rust-faf-mcp (4.3 MB)

Edition: 2024 | LTO: enabled | Strip: symbols

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

Links

Citation

If you use rust-faf-mcp or the .faf / .fafa 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). Why Agents Need a Passport: .fafa — Portable Identity for the Agentic Era. Zenodo. https://doi.org/10.5281/zenodo.21951641

License

MIT


Built by @wolfe_jam | wolfejam.dev

Signals

GitHub stars
4
Forks
1
Last commit
Oct 2026
Weekly downloads
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Delivery
rust-faf-mcp MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
one-faf-rust-faf-mcp
Source
github.com/wolfe-jam/rust-faf-mcp