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Sari - Local Search MCP Server

Project description

Sari (사리)

🇰🇷 한국어 가이드 (Korean Guide)

Sari is a high-performance Local Code Search Agent implementing the Model Context Protocol (MCP). It empowers AI assistants (like Claude, Cursor, Codex) to efficiently navigate, understand, and search large codebases without sending code to external servers.

Key Features:

  • Fast Indexing: SQLite FTS5 + AST-based symbol extraction.
  • 🔍 Smart Search: Hybrid ranking (Keyword + Symbol structure).
  • 🧠 Code Intelligence: Call graphs, snippets management, and domain context archiving.
  • 🔒 Local & Secure: All data remains on your machine. No external API dependency.

🚀 Installation & Setup

Sari supports automatic installation via MCP configuration (Recommended) or manual installation via pip.

Option 1: Automatic Installation (Recommended)

Add the following configuration to your MCP client (Cursor, Claude Desktop, etc.). Sari will be automatically installed (via pip) and updated upon launch.

🍎 macOS / Linux

Cursor / Claude Desktop Config:

{
  "mcpServers": {
    "sari": {
      "command": "bash",
      "args": [
        "-lc",
        "export PATH=$PATH:/usr/local/bin:/opt/homebrew/bin:$HOME/.local/bin && (curl -fsSL https://raw.githubusercontent.com/BaeCheolHan/sari/main/install.py | python3 - -y || true) && exec ~/.local/share/sari/bootstrap.sh --transport stdio"
      ],
      "env": {
        "DECKARD_WORKSPACE_ROOT": "/path/to/your/project",
        "DECKARD_RESPONSE_COMPACT": "1"
      }
    }
  }
}

🪟 Windows (PowerShell)

Cursor / Claude Desktop Config:

{
  "mcpServers": {
    "sari": {
      "command": "powershell",
      "args": [
        "-NoProfile",
        "-ExecutionPolicy", "Bypass",
        "-Command",
        "irm https://raw.githubusercontent.com/BaeCheolHan/sari/main/install.py | python - -y; & $env:LOCALAPPDATA\sari\bootstrap.bat --transport stdio"
      ],
      "env": {
        "DECKARD_WORKSPACE_ROOT": "C:\\path\\to\\your\\project",
        "DECKARD_RESPONSE_COMPACT": "1"
      }
    }
  }
}

Option 2: Manual Installation (Pip)

If you prefer to manage the package manually:

# Install from PyPI
pip install sari

# Run MCP Server
python3 -m sari --transport stdio

⚙️ Configuration Reference

Variables are categorized into Installation-time and Runtime settings.

A. Installation & Bootstrapping

Settings affecting the installation scripts (install.py, bootstrap.sh).

Variable Description Default
XDG_DATA_HOME Custom data directory for installation. Sari installs to $XDG_DATA_HOME/sari. ~/.local/share
DECKARD_SKIP_INSTALL Set 1 to skip automatic pip install/upgrade on startup. Useful for development or offline usage. 0
DECKARD_NO_INTERACTIVE Set 1 to disable interactive prompts during installation (assumes 'yes'). 0

B. System & Runtime

Settings controlling the MCP server loop and behaviors. Add these to your env config.

1. Core & System

Essential settings for basic operation.

Variable Description Default
DECKARD_WORKSPACE_ROOT (Required) Absolute path to the project root. Auto-detected if omitted. Auto-detect
SARI_ROOTS_JSON JSON array of strings for multiple workspace roots. e.g., ["/path/a", "/path/b"] -
DECKARD_DB_PATH Custom path for the SQLite database file. ~/.local/share/sari/data/<hash>/index.db
DECKARD_CONFIG Path to a specific config file to load. ~/.config/sari/config.json
DECKARD_RESPONSE_COMPACT Minify JSON responses (pack format) to save LLM tokens. Set 0 for pretty-print debugging. 1 (Enabled)
DECKARD_FORMAT Output format for CLI tools. pack (text-based) or json. pack

2. Search Engine

Settings to tune search quality and backend behavior.

Variable Description Default
DECKARD_ENGINE_MODE Search backend. embedded uses Tantivy (faster, smart ranking), sqlite uses FTS5 (slower, fallback). embedded
DECKARD_ENGINE_TOKENIZER Tokenizer strategy. auto (detects), cjk (optimized for KR/CN/JP), latin (standard). auto
DECKARD_ENGINE_AUTO_INSTALL Automatically install engine binaries (Tantivy) if missing. 1 (Enabled)
DECKARD_ENGINE_SUGGEST_FILES File count threshold to suggest upgrading to Tantivy engine in status checks. 10000
DECKARD_LINDERA_DICT_PATH Path to custom Lindera dictionary for CJK tokenization (Advanced). -

3. Indexing & Performance

Fine-tune resource usage and concurrency.

Variable Description Default
DECKARD_COALESCE_SHARDS Number of lock shards for indexing concurrency. Increase for massive repos with frequent changes. 16
DECKARD_PARSE_TIMEOUT_SECONDS Timeout per file parsing in seconds. Set 0 to disable timeout. Prevents parser hangs. 0
DECKARD_PARSE_TIMEOUT_WORKERS Worker threads for parsing with timeout. 2
DECKARD_MAX_PARSE_BYTES Max file size to attempt parsing (bytes). Larger files are skipped or sampled. 16MB
DECKARD_MAX_AST_BYTES Max file size to attempt AST extraction (bytes). 8MB
DECKARD_GIT_CHECKOUT_DEBOUNCE Seconds to wait after git checkout before starting bulk indexing. 3.0
DECKARD_FOLLOW_SYMLINKS Follow symbolic links during file scanning. Caution: May cause infinite loops if circular links exist. 0 (Disabled)
DECKARD_READ_MAX_BYTES Max bytes returned by read_file tool. Prevents context overflow. 1MB

4. Network & Security

Connectivity settings for the daemon.

Variable Description Default
DECKARD_DAEMON_HOST Host address for the background daemon. 127.0.0.1
DECKARD_DAEMON_PORT TCP port for the daemon. 47779
DECKARD_HTTP_API_PORT Port for the HTTP API server (optional). 47777
DECKARD_ALLOW_NON_LOOPBACK Allow connections from non-localhost IPs. Security Risk: Only enable in trusted networks. 0 (Disabled)

5. Advanced / Debug

Developer options for debugging and plugin extension.

Variable Description Default
DECKARD_CALLGRAPH_PLUGIN Python module path for custom static analysis plugin. -
DECKARD_DRYRUN_LINT Enable linter checks (ruff/eslint) in dry_run_diff tool. 0
DECKARD_DLQ_POLL_SECONDS Interval to retry failed indexing tasks (Dead Letter Queue). 60
DECKARD_LOG_LEVEL Logging verbosity (DEBUG, INFO, WARNING, ERROR). INFO

🛠️ Usage (MCP Tools)

Once connected, your AI assistant can use these tools:

Core Tools

  • search: Search for code or documentation using keywords or regex.
  • read_file: Read file content (optimized for large files).
  • list_files: List files in the repository.
  • search_symbols: Find classes, functions, or methods by name.
  • read_symbol: Read only the definition of a specific symbol (saves context).

Intelligence Tools

  • call_graph: Analyze function call relationships (upstream/downstream).
  • save_snippet / get_snippet: Save and retrieve important code blocks with tags.
  • archive_context / get_context: Store domain knowledge and design decisions.
  • grep_and_read: Search and read top N files in one go (Composite tool).

🩺 Troubleshooting

Check Status

You can check the daemon status and indexing progress:

# If installed automatically:
~/.local/share/sari/bootstrap.sh status

# If installed via pip:
sari status

Run Doctor

Diagnose issues with your environment or installation:

# If installed automatically:
~/.local/share/sari/bootstrap.sh doctor --auto-fix

# If installed via pip:
sari doctor --auto-fix

Uninstall

To remove Sari, indexed data, and default configs:

# macOS/Linux
curl -fsSL https://raw.githubusercontent.com/BaeCheolHan/sari/main/install.py | python3 - --uninstall

# Windows
irm https://raw.githubusercontent.com/BaeCheolHan/sari/main/install.py | python - --uninstall

To also remove workspace-local caches (if used), pass the workspace root:

curl -fsSL https://raw.githubusercontent.com/BaeCheolHan/sari/main/install.py | python3 - --uninstall --workspace-root /path/to/project

The uninstall command also scans your home directory for .codex/tools/sari caches and removes them (best effort).

If you set SARI_CONFIG or DECKARD_CONFIG to a custom path and want that file removed too, pass:

curl -fsSL https://raw.githubusercontent.com/BaeCheolHan/sari/main/install.py | python3 - --uninstall --force-config

📜 License

Apache License 2.0

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