This MCP integrates semantic search using BERT embeddings with Large Language Models to facilitate natural language file queries in Linux systems. It leverages MCP servers for file system operations, enabling users to perform context-aware, accurate file searches through natural language commands and LLM understanding. Designed for developers and data professionals, it streamlines local file retrieval and management tasks efficiently.
Added on:
Created by:
May 02 2025
This MCP integrates semantic search using BERT embeddings with Large Language Models to facilitate natural language file queries in Linux systems. It leverages MCP servers for file system operations, enabling users to perform context-aware, accurate file searches through natural language commands and LLM understanding. Designed for developers and data professionals, it streamlines local file retrieval and management tasks efficiently.
Added on:
Created by:
May 02 2025
Pruthiraj Jayasingh
Featured
What is File Search Assistant with LLM Integration?
The MCP provides an intelligent file search system that combines semantic understanding with natural language processing. Utilizing BERT embeddings, it performs context-aware searches, while LLM models like Google's Gemini interpret user queries. It features integration with MCP servers for efficient file system operations, automatic file extension inference, and extensibility for additional search capabilities. Suitable for developers, data analysts, and system administrators, it simplifies complex file retrieval tasks on Linux, making file management more intuitive and effective through conversational commands.
Who will use File Search Assistant with LLM Integration?
- Developers
- Data Analysts
- System Administrators
How to use the File Search Assistant with LLM Integration?
- Step 1: Clone the repository from GitHub
- Step 2: Install required dependencies with pip
- Step 3: Configure environment variables, including Gemini API key
- Step 4: Run the main application using 'python main.py'
- Step 5: Enter natural language query for file search when prompted
File Search Assistant with LLM Integration's Core Features & Benefits
The Core Features
- Natural language file search
- Semantic search with BERT embeddings
- LLM integration with Gemini API
- File system operation via MCP server
- Automatic file extension inference
The Benefits
- User-friendly natural language interface
- Accurate and context-aware search results
- Integration with powerful LLMs for query understanding
- Efficient file management in Linux
- Extensible architecture for new features
File Search Assistant with LLM Integration's Main Use Cases & Applications
- Semantic file search for software development
- Automated document retrieval in large repositories
- Natural language interface for system administrators
- Enhanced data exploration for research projects
FAQs of File Search Assistant with LLM Integration
Developer
- Code-Trees
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