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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

RMCP-powered FAF server. 8 tools.

README.md

<!-- faf: rust-faf-mcp | Rust | mcp-server | RMCP — the Rust-native MCP server for FAF (Foundational AI-context Format). Single binary, stdio transport, 4.3 MB stripped. cargo install rust-faf-mcp. Built on the rmcp Rust MCP SDK + faf-rust-sdk. --> <!-- mcp-name: one.faf/rust-faf-mcp -->

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](https://crates.io/crates/rust-faf-mcp) ![FAF](https://builder.faf.one) ![Tests](https://github.com/Wolfe-Jam/rust-faf-mcp) ![IANA](https://www.iana.org/assignments/media-types/application/vnd.faf+yaml) ![License](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.fafCLAUDE.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

License

MIT

---

Built by @wolfe_jam | wolfejam.dev

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