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Persistent project context in Rust. 8 MCP tools via rmcp SDK — parse, validate, score, compress, discover, and token analysis. Single binary, zero config. IANA-
Persistent project context in Rust. 8 MCP tools via rmcp SDK — parse, validate, score, compress, discover, and token analysis. Single binary, zero config. IANA-registered format (application/vnd.faf+yaml). One file, every AI platform.
Stop re-explaining your project to every AI session. One
.faffile 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.
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
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 2021
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.
| 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 |
| 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) |
| 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.
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
tokio single-threaded (current_thread)reqwest async (only used by faf_git for GitHub API)faf-rust-sdk 1.3 for parsing, validation, compression, discoveryrmcp 1.1 with #[tool_router] macro — handles JSON-RPC, schema generation, transportTools return serde_json::Value. The server adapts them to Result<String, String> for rmcp's IntoCallToolResult.
112 tests across 6 files:
cargo test # runs all 112
| 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.
One format, every AI platform.
| Package | Platform | Registry |
|---|---|---|
| rust-faf-mcp | Rust | crates.io |
| claude-faf-mcp | Anthropic | npm + MCP #2759 |
| gemini-faf-mcp | PyPI | |
| grok-faf-mcp | xAI | npm |
| faf-cli | Universal | npm |
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: 2021 | LTO: enabled | Strip: symbols
If rust-faf-mcp has been useful, consider starring the repo — it helps others find it.
application/vnd.faf+yamlMIT
Built by @wolfe_jam | wolfejam.dev
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"rust-faf-mcp-rmcp": {
"command": "npx",
"args": []
}
}
}