# Readonly Filesystem MCP Server

> Use this tool when you need to securely access and retrieve file information within a read-only filesystem, allowing for operations such as file reading, directory listing, file searching, and metadata retrieval. It solves problems related to secure file system access and management, providing a controlled interface for file interactions. The server accepts directory specifications as input and returns relevant file information as output, making it ideal for use cases requiring restricted and secure file system operations.

Canonical page: https://skillsregistry.net/skills/danielsuguimoto-readonly-filesystem-mcp  
JSON: https://api.skillsregistry.net/v1/skills/danielsuguimoto-readonly-filesystem-mcp

## Description

Node.js server implementing Model Context Protocol for secure read-only filesystem operations, allowing Claude to read files, list directories, search files, and get file metadata within specified directories.

## Trust

- **Trust score (0–1):** 0.96
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/b03yztjzhk)
- **Repository:** <https://github.com/danielsuguimoto/readonly-filesystem-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "danielsuguimoto-readonly-filesystem-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/danielsuguimoto-readonly-filesystem-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/danielsuguimoto-readonly-filesystem-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt