file_analysis_mcp
File Analysis MCP Server is a custom-built Model Context Protocol server designed for text file analysis, available as a package on PyPI.
This server is certified by MCP Hub and listed as a trusted MCP server.
File Analysis MCP Server
A custom-built MCP (Model Context Protocol) server for text file analysis, also published as a package to PyPI.
Table of Contents
- Introduction
- Features
- Installation and Setup from GitHub
- Claude Desktop Integration
- Installation from Package
Introduction
What is MCP?
Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). It creates a consistent interface for AI models like Claude to interact with external tools, data sources, and services.
MCP follows a client-server architecture:
- MCP Hosts: Programs like Claude Desktop that initiate connections
- MCP Clients: Protocol clients inside the host application
- MCP Servers: Lightweight programs (like this one) that expose capabilities
- Local Data Sources: Your computer's files, databases, and services
Why MCP?
MCP helps you build agents and complex workflows with LLMs by providing:
- Standardized interfaces to connect AI models to different data sources
- The flexibility to switch between LLM providers
- Best practices for secure data access
Features
This File Analysis MCP Server provides:
- Text analysis tools (word count, character frequency, etc.)
- File reading capabilities
- Directory listing
- File content access via MCP resources
Text Analysis Tool (analyze_text)
File Reader Tool (read_file)
Directory Browsing Tool (list_files)
Installation and Setup from GitHub
Step 1: Clone the Repository
Start by cloning the repository to your local machine:
git clone https://github.com/yourusername/file-analysis-mcp.git
cd file-analysis-mcp
Step 2: Set Up UV Package Manager
This project uses UV, a fast Python package manager. If you don't have it installed:
For MacOS/Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
For Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Remember to restart your terminal after installing UV.
Step 3: Create a Virtual Environment
# Create and activate a virtual environment
uv venv
For MacOS/Linux:
source .venv/bin/activate
For Windows:
.venv\Scripts\activate
Step 4: Install Dependencies
# Install the required dependencies
uv pip install "mcp[cli]"
Testing and Debugging
Running with the MCP Inspector:
uv run mcp dev path/to/your/server/file
Claude Desktop Integration
The real power of your File Analysis server comes when you connect it to Claude Desktop!
Setting Up with Claude Desktop
-
Make sure Claude Desktop is installed
- Download from Claude.ai if you don't have it
-
Locate the configuration file:
- MacOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%AppData%\Claude\claude_desktop_config.json
If the file doesn't exist, create it.
- MacOS:
-
Add your server configuration:
For MacOS/Linux:
{ "mcpServers": { "file-analysis": { "command": "uv", "args": [ "--directory", "/ABSOLUTE/PATH/TO/file-analysis-mcp", "run", "server.py" ] } } }For Windows:
{ "mcpServers": { "file-analysis": { "command": "uv", "args": [ "--directory", "C:\\ABSOLUTE\\PATH\\TO\\file-analysis-mcp", "run", "server.py" ] } } }Important: Replace the path with the actual absolute path to where you cloned the repository. Do not use relative paths.
-
Restart Claude Desktop
- Close and reopen the application completely
-
Verify the connection
- Look for the tools icon (hammer) in the Claude interface
- Your tools should appear in the list when clicking this icon
Tips for Using Your Server
- File Paths: Always provide absolute file paths for best results
- Large Files: Break up analysis of very large files into smaller chunks
- Permissions: Ensure Claude has permission to access the files/directories you're analyzing
Installation from Package
From PyPI (Recommended)
The simplest way to install File Analysis MCP Server is from PyPI:
pip install file-analysis-mcp
Or using UV (recommended):
uv pip install file-analysis-mcp
Add your server configuration
{
"mcpServers": {
"mcp-server": {
"command": "uv",
"args": [
"run",
"mcp-server"
]
}
}
}
