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
- 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
- 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 stringfile_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 readencoding(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 listmax_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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file p6plab_datasage-1.0.3.tar.gz.
File metadata
- Download URL: p6plab_datasage-1.0.3.tar.gz
- Upload date:
- Size: 300.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.9.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
534f6eebc371fc547a0be8e721652a55b8ac26dbcaea123b0e3df1c560c88dfd
|
|
| MD5 |
cf3290144afaf2281444c66cc267220a
|
|
| BLAKE2b-256 |
c441f81913ec967bb7a69e584078514fcb5f17dbbd2ec8235d846dd12dd6675e
|
File details
Details for the file p6plab_datasage-1.0.3-py3-none-any.whl.
File metadata
- Download URL: p6plab_datasage-1.0.3-py3-none-any.whl
- Upload date:
- Size: 29.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.9.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9296f54f5dfb99370586688d879dbb38fb2ce0fe8fc8ff41ffe4994ec99d8dee
|
|
| MD5 |
9c1835eb760d54fc6077497175df1589
|
|
| BLAKE2b-256 |
e0e8b54a0cc57738004d2b2d16c2c898a06de5e11fa289f924fe56322dbba499
|