PyWry vs filesystem
Side-by-side comparison to help you pick between these two MCP servers.
PyWry by deeleeramone | filesystem by modelcontextprotocol | |
|---|---|---|
| Stars | ★ 81 | ★ 85,748 |
| 30d uses | — | — |
| Score | 46 | 77 |
| Official | — | ✓ |
| Categories | AI / LLM ToolsDeveloper ToolsProductivity | File SystemDeveloper ToolsProductivity |
| Language | Python | TypeScript |
| Last commit | this month | this month |
PyWry · Summary
PyWry is a cross-platform rendering engine that provides MCP server tools for creating interactive widgets and dashboards.
filesystem · Summary
A feature-rich MCP server for filesystem operations with dynamic directory access control.
PyWry · Use cases
- Create data visualization dashboards in AI workflows and share them as HTML artifacts
- Build interactive chat interfaces with AI agents using multiple LLM providers
- Generate responsive UI prototypes that can be deployed as desktop apps or web services
filesystem · Use cases
- Enable AI models to read and write project files during development
- Allow Claude or other MCP clients to browse and analyze codebases
- Provide secure sandboxed access to specific directories for content generation
PyWry · Install
Install PyWry with MCP support:
pip install 'pywry[mcp]'Start the MCP server:
pywry mcp --transport stdioFor Claude Desktop, add to config.json:
{
"mcpServers": {
"pywry": {
"command": "pywry",
"args": ["mcp", "--transport", "stdio"]
}
}
}filesystem · Install
Installation
Using NPX
{
"mcpServers": {
"filesystem": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-filesystem",
"/path/to/allowed/directory"
]
}
}
}Using Docker
{
"mcpServers": {
"filesystem": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"--mount", "type=bind,src=/path/to/allowed/dir,dst=/projects/allowed/dir",
"mcp/filesystem",
"/projects"
]
}
}
}VS Code Extension
Click the installation buttons in the README to install directly in VS Code.