rust-faf-mcp

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

The one.faf Edition (v0.4.0) — one.faf/rust-faf-mcp · rmcp 3.0.1 (MCP Tier 1 foundation) · solid cargo-native Rust MCP for Rust devs

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.

Crates.io FAF Tests IANA License

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

cargo install rust-faf-mcp

Then point any MCP client at it:

# Claude Code
claude mcp add faf rust-faf-mcp

// WARP / Cursor / Zed / Claude Desktop — any stdio MCP client
{
  "mcpServers": {
    "faf": {
      "command": "rust-faf-mcp"
    }
  }
}

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

Or via Homebrew (macOS, pre-built):

brew install Wolfe-Jam/faf/rust-faf-mcp

One command, done forever

faf_auto detects your project, creates a .faf, enhances it to max score, and syncs CLAUDE.md — in one shot:

faf_auto complete
━━━━━━━━━━━━━━━━━
Score: 0% → 85% (+85) ◇ BRONZE
Steps:
  1. Created project.faf
  2. Second enhancement pass
  3. Created CLAUDE.md

Path: /home/user/my-project

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_tool: cargo

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

Tools

Create & Detect

Tool	What it does
faf_auto	Zero to AI context in one command — init, enhance, sync, score, done
faf_init	Create or enhance project.faf from Cargo.toml, package.json, pyproject.toml, or go.mod
faf_git	Generate project.faf from any GitHub repo URL — no clone needed
faf_discover	Walk up the directory tree to find the nearest project.faf

Score & Validate

Tool	What it does
faf_score	Score AI-readiness 0-100% with field-level breakdown
faf_sync	Sync project.faf → CLAUDE.md (preserves existing content)

Optimize

Tool	What it does
faf_read	Parse and display project.faf contents
faf_compress	Compress .faf for token-limited contexts (minimal / standard / full)
faf_tokens	Estimate token count at each compression level

faf_init is iterative — run it again and it fills in what's missing. Score goes up each time.

Architecture

src/
├── main.rs      # ~20 lines — tokio entry, rmcp stdio transport
├── server.rs    # FafServer: #[tool_router], ServerHandler, resources
└── tools.rs     # Business logic — all 9 tools, 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 1.3 (Cargo pin — parse / validate / compress / discover; foundation 3.x lives in faf-rust)
• 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

112 tests across 6 files:

cargo test    # runs all 112

# 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

File	Tests	Coverage
mcp_protocol.rs	9	Init handshake, tools/list, resources, schema validation, ID preservation
tools_functional.rs	25	All 9 tools — happy path, error paths, language detection
tier1_security.rs	12	Path traversal, null bytes, shell injection, oversized input, malformed JSON
tier2_engine.rs	35	Corrupt YAML, sync replacement, pipelines, dual manifests, legacy filenames, direct paths
tier3_edge_cases.rs	10	Unicode, CJK, score boundaries, unknown fields, GitHub URL parsing
tier4_aero.rs	21	Manifest structure, version sync, server.json, manifest-server cross-validation

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.

Package	Platform	Registry
rust-faf-mcp	Rust	crates.io
claude-faf-mcp	Anthropic	npm + MCP #2759
gemini-faf-mcp	Google	PyPI
grok-faf-mcp	xAI	npm
faf-cli	Universal	npm

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

• crates.io/crates/rust-faf-mcp
• faf-rust-sdk — the parser this depends on
• faf.one — FAF home
• IANA registration — application/vnd.faf+yaml
• MCP Registry name: mcp-name: one.faf/rust-faf-mcp
• CHANGELOG

License

MIT

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Built by @wolfe_jam | wolfejam.dev