The Privacy Problem with Cloud AI

# Install Ollama (macOS/Linux)
curl -fsSL https://ollama.com/install.sh | sh

# Pull a model
ollama pull llama3.2

# Test it
ollama run llama3.2 "What is 2+2?"

"""Private Local MCP Server — Safe file and notes access."""

from pathlib import Path
from mcp.server import MCPServer

mcp = MCPServer("Private Assistant")

# ── Safety: Restrict to specific directories ──────────────
NOTES_DIR = Path("./notes").resolve()
DOCS_DIR = Path("./documents").resolve()
NOTES_DIR.mkdir(exist_ok=True)
DOCS_DIR.mkdir(exist_ok=True)


def safe_path(user_path: str, base: Path) -> Path | None:
    """Ensure path stays within allowed directory."""
    try:
        resolved = (base / user_path).resolve()
        return resolved if resolved.is_relative_to(base) else None
    except (ValueError, OSError):
        return None


@mcp.tool()
def read_document(name: str) -> str:
    """Read a document from the allowed directory."""
    path = safe_path(name, DOCS_DIR)
    if path is None:
        return "Error: Access denied"
    if not path.exists():
        return f"Error: '{name}' not found"
    if path.stat().st_size > 500_000:
        return "Error: File too large (max 500KB)"
    return path.read_text(encoding="utf-8")


@mcp.tool()
def search_notes(query: str) -> str:
    """Search notes for a query."""
    results = []
    for f in NOTES_DIR.rglob("*.md"):
        try:
            content = f.read_text(encoding="utf-8")
            for i, line in enumerate(content.splitlines(), 1):
                if query.lower() in line.lower():
                    results.append(f"{f.name}:{i}: {line.strip()}")
        except (OSError, UnicodeDecodeError):
            continue
    return "\n".join(results[:10]) or f"No results for '{query}'"


@mcp.tool()
def create_note(title: str, content: str) -> str:
    """Create a new note."""
    path = NOTES_DIR / f"{title.replace(' ', '_').lower()}.md"
    path.write_text(f"# {title}\n\n{content}", encoding="utf-8")
    return f"Created: {path.name}"


@mcp.tool()
def list_documents() -> str:
    """List available documents."""
    files = [f.name for f in DOCS_DIR.rglob("*") if f.is_file()]
    return "\n".join(files) or "No documents found"


@mcp.resource("private://status")
def system_status() -> str:
    """Get system status."""
    import json
    return json.dumps({
        "documents": len(list(DOCS_DIR.rglob("*"))),
        "notes": len(list(NOTES_DIR.rglob("*"))),
        "llm": "local (ollama)",
        "internet": "not required"
    })


if __name__ == "__main__":
    print(f"Documents: {DOCS_DIR}")
    print(f"Notes: {NOTES_DIR}")
    mcp.run()

// Claude Desktop config
{
  "mcpServers": {
    "private-assistant": {
      "command": "python",
      "args": ["/path/to/private_server.py"],
      "env": {}
    }
  }
}

User: "What's in my project notes?"

Agent (using MCP):
  1. Calls list_documents()
  2. Calls search_notes("project")
  3. Returns relevant notes

User: "Create a note about today's meeting"

Agent (using MCP):
  1. Calls create_note("Meeting Notes", "Content...")
  2. Confirms note created

All data stays on your machine.