File Manage

Provides a Windows-local MCP server to organize files with intelligent analysis, safe dry-run, and sandboxed operations.

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GitHub Stars

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Language

6 months ago

First Indexed

3 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "duaghwls-filemanagemcp": {
      "command": "uv",
      "args": [
        "--directory",
        "{your_path}/FileManageMCP",
        "run",
        "python",
        "server.py"
      ]
    }
  }
}

You run a Windows-based MCP server that helps your large language model organize and manage your local file system. It analyzes directories, previews file content, reads image metadata, suggests meaningful file names, groups related files, and safely performs file operations with built-in dry-run and sandbox safeguards.

How to use

You will run the MCP server locally and interact with it through your MCP client. Start by setting up a dedicated work area, then use the available analysis and organization tools to inspect, rename, group, and move files in a controlled, auditable flow.

How to install

Prerequisites you need before installing the MCP server are clear and straightforward.

Configuration and safety

The server runs in a guarded mode by default to help prevent accidental data changes. You can switch to real execution once you verify the planned changes. The work area is restricted to a specified directory, protecting system folders and sensitive areas.

Usage workflow example

Prepare your working directory and start the MCP server using the configured path.

Project structure

The MCP server is designed to organize and analyze files within a Windows environment, providing a set of tools to inspect directories, read files, extract metadata, and perform safe file operations with dry-run and sandbox features.

Available tools

tool_set_dry_run

Configure Dry Run mode to simulate all modifications without changing any files; default is enabled.

tool_get_status

Check current configuration and Dry Run status to verify safe operation before applying changes.

tool_configure_workspace

Define and restrict the working sandbox to a specific directory to prevent access to restricted paths.

tool_list_directory

List directory contents with date information to understand structure and timing.

tool_read_file_snippet

Preview file contents to gauge relevance and determine appropriate renaming or grouping.

tool_get_image_metadata

Extract image EXIF data to help determine shooting date and context for file organization.

tool_analyze_directory_structure

Analyze the directory tree to identify potential organization improvements and issues.

tool_find_files_needing_rename

Identify files with unclear names that should be renamed for consistency.

tool_suggest_filename_from_content

Generate suggested filenames based on file content summaries.

tool_get_image_for_analysis

Provide image-derived data for analysis when visual context informs file organization.

tool_analyze_file_relationships

Analyze relationships between files to propose logical grouping.

tool_move_file

Move a file to a new location as part of a reorganization workflow (Dry Run supported).

tool_rename_file

Rename a file or folder to a clearer, standardized name (Dry Run supported).

tool_rename_with_suggestion

Apply an advanced, LLM-derived name suggestion for files or folders (Dry Run supported).

tool_create_folder

Create a new folder within the sandbox to host grouped files.

tool_group_files_into_folder

Move related files into a newly created folder to form cohesive groups.

tool_batch_rename_with_date

Add date prefixes to multiple files in a batch operation to enforce naming rules.