pydantic-rpc vs filesystem
Side-by-side comparison to help you pick between these two MCP servers.
pydantic-rpc by i2y | filesystem by modelcontextprotocol | |
|---|---|---|
| Stars | ★ 74 | ★ 85,748 |
| 30d uses | — | — |
| Score | 45 | 77 |
| Official | — | ✓ |
| Categories | Developer ToolsAI / LLM Tools | File SystemDeveloper ToolsProductivity |
| Language | Python | TypeScript |
| Last commit | 3 mo ago | this month |
pydantic-rpc · Summary
PydanticRPC rapidly exposes Pydantic models as gRPC, ConnectRPC, and MCP services without protobuf files.
filesystem · Summary
A feature-rich MCP server for filesystem operations with dynamic directory access control.
pydantic-rpc · Use cases
- Building AI services with tools exposed through MCP protocol
- Creating gRPC services without writing protobuf files
- Developing HTTP-based RPC services using Connect-RPC
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
pydantic-rpc · Install
Install PydanticRPC via pip:
pip install pydantic-rpcFor CLI support:
pip install pydantic-rpc-cliTo use in Claude Desktop, add to config.json:
{
"mcpServers": {
"pydantic-rpc": {
"command": "python",
"args": ["-m", "pydantic_rpc.server"],
"env": {
"PYDANTIC_RPC_PACKAGE_NAME": "my.services"
}
}
}
}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.