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MCP server for secure local file system access

Project description

DataSage MCP Server

DataSage is a Model Context Protocol (MCP) server that provides AI assistants with secure access to local file systems. It enables generative AI tools like Amazon Q, Claude Desktop, and other MCP-compatible clients to search, read, and navigate local files and directories through a standardized interface.

Features

  • Secure File Access: Configurable path restrictions prevent access outside specified directories
  • Full-Text Search: Search file contents and filenames with fuzzy matching, regex, and exact matching
  • Semantic Search: Conceptual similarity matching using sentence embeddings with persistent caching and real-time directory snapshot comparison for comprehensive file system monitoring
  • Performance Optimization: Built-in timing metrics, automatic cache invalidation, embedding persistence, smart caching with snapshot awareness, and real-time file system change detection
  • Directory Traversal: Navigate directory structures with configurable depth limits
  • Text File Support: Automatic detection and handling of text-based files with encoding support
  • Graceful Exit: Proper signal handling (Ctrl+C) with resource cleanup
  • MCP Compliant: Follows Model Context Protocol specification for seamless AI integration
  • FastMCP v2: Built on the latest FastMCP framework for optimal performance

Installation

Install DataSage using uvx (recommended):

uvx p6plab-datasage

Or install with pip:

pip install p6plab-datasage

Quick Start

  1. Create a configuration file (datasage.yaml):
server:
  name: "My DataSage"
  description: "Local file server for AI assistants"

paths:
  - path: "~/Documents"
    description: "Personal documents"
  - path: "~/Code"
    description: "Source code files"

settings:
  max_depth: 10
  max_file_size: 10485760  # 10MB
  1. Start the server:
# STDIO transport (for Claude Desktop, etc.)
uvx p6plab-datasage

# HTTP transport (for web-based clients)
uvx p6plab-datasage --transport http --port 8000

# Custom configuration
uvx p6plab-datasage --config my-config.yaml

Configuration

Configuration File Format

DataSage uses YAML configuration files with the following structure:

server:
  name: "DataSage"                    # Server name
  description: "File server for AI"   # Server description

paths:                                # Allowed file paths
  - path: "~/Documents"
    description: "Documents folder"
  - path: "/Users/shared/projects"
    description: "Shared projects"

settings:
  max_depth: 10                       # Maximum directory depth
  max_file_size: 10485760            # Maximum file size (10MB)
  text_detection: "auto"             # Text file detection method
  excluded_extensions:               # Binary file extensions to skip
    - ".exe"
    - ".jpg"
    - ".pdf"

tools:
  search:
    description: "Search files"       # Tool descriptions
    max_results: 50
  get_page:
    description: "Get file content"
  get_page_children:
    description: "List directory contents"

search:
  fuzzy_threshold: 0.8               # Fuzzy matching threshold
  enable_regex: true                 # Enable regex search
  index_content: true                # Index file contents
  enable_semantic: true              # Enable semantic search
  semantic_model: "paraphrase-MiniLM-L3-v2"  # Lightweight model (~17MB)

Environment Variables

Override configuration with environment variables (higher priority than YAML):

Server Configuration:

export DATASAGE_NAME="Custom DataSage"
export DATASAGE_DESCRIPTION="Custom description"

Path Configuration:

export DATASAGE_PATHS="~/Documents,~/Code,/shared/projects"

Settings Configuration:

export DATASAGE_MAX_DEPTH=5                    # Maximum directory depth (1-20)
export DATASAGE_MAX_FILE_SIZE=5242880          # Maximum file size in bytes
export DATASAGE_TEXT_DETECTION="auto"          # Text detection: "auto", "extension", "content"
export DATASAGE_EXCLUDED_EXTENSIONS=".exe,.bin,.jpg,.png"  # Comma-separated extensions

Tool Configuration:

export DATASAGE_SEARCH_MAX_RESULTS=100         # Maximum search results
export DATASAGE_TOOL_SEARCH_DESC="Search my files"
export DATASAGE_TOOL_GET_PAGE_DESC="Get file content"
export DATASAGE_TOOL_GET_PAGE_CHILDREN_DESC="List directory contents"

Search Configuration:

export DATASAGE_FUZZY_THRESHOLD=0.9            # Fuzzy matching threshold (0.0-1.0)
export DATASAGE_ENABLE_REGEX=true              # Enable regex search (true/false)
export DATASAGE_INDEX_CONTENT=true             # Index file contents (true/false)
export DATASAGE_ENABLE_SEMANTIC=true           # Enable semantic search (true/false)
export DATASAGE_SEMANTIC_MODEL="paraphrase-MiniLM-L3-v2"  # Semantic model name

Complete Example:

export DATASAGE_NAME="My Custom DataSage"
export DATASAGE_PATHS="~/Documents,~/Code"
export DATASAGE_MAX_DEPTH=5
export DATASAGE_ENABLE_SEMANTIC=true
export DATASAGE_FUZZY_THRESHOLD=0.9

uvx p6plab-datasage

Available Tools

DataSage provides three MCP tools:

1. search

Search files by content or filename with multiple matching algorithms.

Parameters:

  • query (required): Search query string
  • file_type (optional): File extension filter (e.g., ".py", ".md")
  • search_type (optional): "content", "filename", or "both" (default: "both")
  • match_type (optional): Matching algorithm (auto-defaults to best available):
    • semantic: AI-powered conceptual similarity (best for understanding meaning)
    • fuzzy: Handles typos and similar words (good for approximate matches)
    • exact: Precise string matching (fastest, most restrictive)
    • regex: Pattern matching with regular expressions (for advanced patterns)
  • max_results (optional): Maximum results to return (default: 20)

2. get_page

Retrieve the content of a specific file.

Parameters:

  • path (required): File path to read
  • encoding (optional): Text encoding (default: "utf-8")

3. get_page_children

List the contents of a directory with optional recursion.

Parameters:

  • path (required): Directory path to list
  • max_depth (optional): Maximum recursion depth (default: 1)
  • include_files (optional): Include files in results (default: true)
  • include_dirs (optional): Include directories in results (default: true)
  • file_filter (optional): File extension filter

Usage Examples

With Claude Desktop

Add to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "datasage": {
      "command": "uvx",
      "args": ["p6plab-datasage", "--config", "/path/to/datasage.yaml"]
    }
  }
}

With FastMCP Client

import asyncio
from fastmcp import Client

async def main():
    async with Client("uvx p6plab-datasage") as client:
        # Search for Python files
        result = await client.call_tool("search", {
            "query": "function",
            "file_type": ".py",
            "search_type": "content"
        })
        print(result.content[0].text)
        
        # Semantic search for governance concepts
        result = await client.call_tool("search", {
            "query": "data privacy compliance",
            "search_type": "semantic",
            "max_results": 10
        })
        print(result.content[0].text)

asyncio.run(main())

Command Line Options

# Basic usage
uvx p6plab-datasage

# HTTP server
uvx p6plab-datasage --transport http --port 8000

# Custom configuration
uvx p6plab-datasage --config /path/to/config.yaml

# Bind to all interfaces
uvx p6plab-datasage --transport http --host 0.0.0.0 --port 8000

# Show help
uvx p6plab-datasage --help

Security

DataSage implements multiple security measures:

  • Path Validation: Only allows access to explicitly configured paths
  • Directory Traversal Protection: Prevents ../ attacks
  • File Type Filtering: Automatically excludes binary files
  • Size Limits: Configurable maximum file sizes
  • Permission Checking: Respects file system permissions

Development

Running from Source

git clone <repository>
cd datasage
pip install -e .
python -m p6plab_datasage.server --config examples/datasage.yaml

Building and Publishing

# Build package
./scripts/build.sh

# Publish to Test PyPI (default)
./scripts/publish.sh

# Publish to main PyPI
./scripts/publish.sh --main

Running Tests

Install test dependencies:

pip install -e ".[dev]"

Run all tests:

# Basic test run
pytest

# Verbose output
pytest -v

# Parallel execution (recommended)
pytest -n auto

# With coverage
pytest --cov=src/p6plab_datasage

# Quick summary
pytest --tb=no -q

Using UV (recommended):

# Run all tests with parallel execution
uv run pytest tests/ -n auto -v

# Quick test run
uv run pytest tests/ --tb=no -q

Test Results:

  • 26/26 tests passing (100% success rate)
  • Complete coverage of all functionality
  • Parallel execution with proper test isolation

Using FastMCP CLI

fastmcp run src/p6plab_datasage/server.py
fastmcp run src/p6plab_datasage/server.py --transport http --port 8000

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit issues and pull requests.

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