Large File MCP Server

A Model Context Protocol (MCP) server for intelligent handling of large files with smart chunking, navigation, and streaming capabilities.

Features

• Smart Chunking - Automatically determines optimal chunk size based on file type

• Intelligent Navigation - Jump to specific lines with surrounding context

• Powerful Search - Regex support with context lines before/after matches

• File Analysis - Comprehensive metadata and statistical analysis

• Memory Efficient - Stream files of any size without loading into memory

• Performance Optimized - Built-in LRU caching for frequently accessed chunks

• Type Safe - Written in TypeScript with strict typing

• Cross-Platform - Works on Windows, macOS, and Linux

Installation

Or use directly with npx:

Quick Start

Claude Code CLI

Add the MCP server using the CLI:

Verify installation:

Remove if needed:

MCP Scopes:

• local - Available only in the current project directory

• user - Available globally for all projects

• project - Defined in .mcp.json for team sharing

Claude Desktop

Add to your claude_desktop_config.json:

Config file locations:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

• Windows: %APPDATA%\Claude\claude_desktop_config.json

Restart Claude Desktop after editing.

Other AI Platforms

Gemini:

Usage

Once configured, you can use natural language to interact with large files:

Available Tools

read_large_file_chunk

Read a specific chunk of a large file with intelligent chunking.

Parameters:

• filePath (required): Absolute path to the file

• chunkIndex (optional): Zero-based chunk index (default: 0)

• linesPerChunk (optional): Lines per chunk (auto-detected if not provided)

• includeLineNumbers (optional): Include line numbers (default: false)

Example:

search_in_large_file

Search for patterns in large files with context.

Parameters:

• filePath (required): Absolute path to the file

• pattern (required): Search pattern

• caseSensitive (optional): Case sensitive search (default: false)

• regex (optional): Use regex pattern (default: false)

• maxResults (optional): Maximum results (default: 100)

• contextBefore (optional): Context lines before match (default: 2)

• contextAfter (optional): Context lines after match (default: 2)

Example:

get_file_structure

Analyze file structure and get comprehensive metadata.

Parameters:

• filePath (required): Absolute path to the file

Returns: File metadata, line statistics, recommended chunk size, and sample lines.

navigate_to_line

Jump to a specific line with surrounding context.

Parameters:

• filePath (required): Absolute path to the file

• lineNumber (required): Line number to navigate to (1-indexed)

• contextLines (optional): Context lines before/after (default: 5)

get_file_summary

Get comprehensive statistical summary of a file.

Parameters:

• filePath (required): Absolute path to the file

Returns: File metadata, line statistics, character statistics, and word count.

stream_large_file

Stream a file in chunks for processing very large files.

Parameters:

• filePath (required): Absolute path to the file

• chunkSize (optional): Chunk size in bytes (default: 64KB)

• startOffset (optional): Starting byte offset (default: 0)

• maxChunks (optional): Maximum chunks to return (default: 10)

Supported File Types

The server intelligently detects and optimizes for:

• Text files (.txt) - 500 lines/chunk

• Log files (.log) - 500 lines/chunk

• Code files (.ts, .js, .py, .java, .cpp, .go, .rs, etc.) - 300 lines/chunk

• CSV files (.csv) - 1000 lines/chunk

• JSON files (.json) - 100 lines/chunk

• XML files (.xml) - 200 lines/chunk

• Markdown files (.md) - 500 lines/chunk

• Configuration files (.yml, .yaml, .sh, .bash) - 300 lines/chunk

Configuration

Customize behavior using environment variables:

Example with custom settings (Claude Desktop):

Example with custom settings (Claude Code CLI):

Examples

Analyzing Log Files

The AI will use the search tool to find patterns and provide context around each match.

Code Navigation

Uses regex search to locate function definitions with surrounding code context.

CSV Data Exploration

Returns metadata, line count, sample rows, and recommended chunk size.

Large File Processing

Uses streaming mode to handle very large files efficiently.

Performance

Caching

• LRU Cache with configurable size (default 100MB)

• TTL-based expiration (default 5 minutes)

• 80-90% hit rate for repeated access

• Significant performance improvement for frequently accessed files

Memory Management

• Streaming architecture - files are read line-by-line, never fully loaded

• Configurable chunk sizes - adjust based on your use case

• Smart buffering - minimal memory footprint for search operations

File Size Handling

Development

Building from Source

Development Mode

Project Structure

Troubleshooting

File not accessible

Ensure the file path is absolute and the file has read permissions:

Out of memory

1. Reduce CHUNK_SIZE environment variable

2. Disable cache with CACHE_ENABLED=false

3. Use stream_large_file for very large files

Slow search performance

1. Reduce maxResults parameter

2. Use startLine and endLine to limit search range

3. Ensure caching is enabled

Claude Code CLI: MCP server not found

Check if the server is installed:

If not listed, reinstall:

Check server health:

Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

Development Workflow

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Ensure code builds and lints successfully

5. Submit a pull request

See CONTRIBUTING.md for detailed guidelines.

License

MIT

Support

• Issues: GitHub Issues

• Documentation: This README and inline code documentation

• Examples: Check the examples/ directory

Acknowledgments

Built with the Model Context Protocol SDK.

Made for the AI developer community.