Files Stdio MCP Server
F

Files Stdio MCP Server

An MCP server that provides sandboxed file access, supporting directory exploration, file reading, content search, and secure editing, suitable for AI agents to manage text file collections.
2.5 points
4.3K

What is Files MCP Server?

Files MCP Server is a file system access tool specifically designed for AI assistants. It allows AI assistants to interact with your file system in a controlled environment, including browsing the folder structure, reading file contents, searching for specific text, and securely editing files. All operations are performed within a preset sandbox directory to ensure the security of other parts of the system.

How to use Files MCP Server?

Using Files MCP Server requires three basic steps: First, configure the server connection in your AI client (such as Claude Desktop or Cursor); then, set the directory paths that are allowed to be accessed; finally, the AI assistant can operate on files through specific tool commands. All operations follow the security principle of 'browse first, then edit'.

Use cases

Files MCP Server is particularly suitable for the following scenarios: managing Obsidian knowledge bases, organizing document projects, batch processing note files, searching for and replacing text content, automating file organization tasks, etc. It enables AI assistants to interact with the file system like humans, but more efficiently and accurately.

Main features

Directory browsing
View the folder contents in a tree structure, showing the number of files, sizes, and modification times to help AI assistants understand the file organizational structure.
File reading
Read the contents of text files and display line numbers, while generating a file checksum for subsequent secure editing operations.
Advanced search
Supports multiple search methods: search by file name pattern, search by text content (supports literal matching, regular expressions, and fuzzy matching).
Preset patterns
Built - in dedicated search patterns for Obsidian/Markdown, such as wiki links, tags, task lists, headings, etc., without the need to write complex regular expressions.
Safe editing
Verify through the checksum to ensure that the file has not been modified before editing. Supports preview mode to view the differences in changes and prevent accidental overwriting.
Batch operations
Supports batch replacement of all matching items in a single file to improve the efficiency of batch modifications.
Multi - directory mounting
Can access multiple directories simultaneously, with each directory serving as an independent virtual mount point for convenient management of different projects.
Sandbox protection
Strictly restricts AI assistants to only access pre - configured directories and prevents access to other parts of the system to ensure security.
Advantages
Secure and controllable: The sandbox mechanism ensures that AI assistants can only access specified directories and will not affect other files in the system.
Intuitive operation: AI assistants can browse before operating, just like humans, to avoid misoperations caused by incorrect paths.
Safe editing: The checksum mechanism prevents conflicts caused by other programs modifying files during editing.
Preview function: Supports the dry - run mode to view the differences in changes before making actual modifications and reduce errors.
Powerful search: Supports multiple search modes and preset templates, especially suitable for processing Markdown and note files.
Error recovery: Detailed error prompts and recovery suggestions help AI assistants recover from operation errors.
Limitations
Limited to text files: Cannot handle binary files (such as pictures, videos, compressed packages, etc.).
File size limit: The default limit is 1MB, and large files require configuration adjustment.
Requires configuration: The directories allowed to be accessed need to be set in advance and cannot access arbitrary locations temporarily.
Learning curve: AI assistants need to follow a specific operation process (read first, then write).
Network limitation: Only supports the local file system and cannot directly access network storage.

How to use

Install the server
Download the Files MCP Server code and install the dependencies.
Configure the access directory
Create a.env file and set the directory paths that the AI assistant can access.
Configure the AI client
Add the server configuration in clients that support MCP, such as Claude Desktop or Cursor.
Start using
Start the AI client, and now you can instruct the AI assistant to operate on files.

Usage examples

Organize the Obsidian note library
The AI assistant helps you organize the cluttered Obsidian notes, reorganize the folder structure, and update internal links.
Batch update task status
Mark specific tasks in multiple files as completed or update task descriptions.
Document link repair
Batch update old links in documents to new links to maintain the consistency of references between documents.
Content search and analysis
Search for content on specific topics in a large number of documents, perform analysis and summarization.

Frequently Asked Questions

Is this tool safe? Will it allow the AI to delete my important files?
Why does the AI assistant need to read the file before editing?
Can I let the AI access multiple different folders?
Which file types are supported for search and editing?
What should I do if the AI makes an error when operating on a file?
How to install the MCP Bundle version?

Related resources

Model Context Protocol official documentation
Understand the basic concepts and working principles of the MCP protocol.
GitHub repository
Get the latest code, submit issues, and view the update log.
MCP Bundles specification
Understand the MCP Bundle format and installation mechanism.
Claude Desktop MCP configuration guide
Learn how to configure the MCP server in Claude Desktop.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "filesystem": {
      "command": "bun",
      "args": ["run", "/absolute/path/to/files-mcp/src/index.ts"],
      "env": {
        "FS_ROOTS": "/Users/you/vault,/Users/you/docs"
      }
    }
  }
}

{
  "mcpServers": {
    "filesystem": {
      "command": "bun",
      "args": ["run", "/path/to/files-mcp/src/index.ts"],
      "env": {
        "FS_ROOTS": "/Users/me/vault"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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