Code Embeddings

Kodit

Enhances local code repositories by leveraging tree-sitter analysis and semantic embeddings to support a unique hybrid search method that blends vector similarity with keyword matching, empowering contextual code retrieval.

Code Indexer

Facilitates quick and effective code search and analysis for software development projects by utilizing embedding models and vector databases to index and fetch code snippets.

Code Context (Semantic Code Search)

Facilitates advanced code exploration and comprehension through the replication of git repositories, segmentation of code into meaningful sections, and creation of representations for simplified natural language search in extensive code repositories.

Codebase Insight

Enhance your software analysis with advanced code insights using a cutting-edge Model Context Protocol (MCP). Uncover patterns, grasp architecture nuances, and streamline knowledge organization. Leveraging a robust FastAPI server and seamless Qdrant vector database fusion for unparalleled efficiency. Elevate your development process with MCP's exceptional capabilities.

RAG Documentation Search

Enhances document search with semantic vectors for contextually relevant results from specified document repositories.

RAGDocs (Vector Documentation Search)

Unlock the ability to search and retrieve semantic documentation effortlessly through vector databases. Get URL extraction, source oversight, and index queuing, paired with diverse embedding providers such as Ollama and OpenAI.

Chat Analysis

Enhance chat analysis capabilities with Model Context Protocol (MCP), utilizing vector embeddings alongside knowledge graphs for tasks such as sentiment analysis, topic modeling, and tracking user behavior patterns.

Simple File Vector Store

Enhances local file and directory search through vector embeddings and smart storage methods, boosting semantic search functionality.

Code2Prompt

Enhance intricate software projects into well-organized briefs tailored for language models, enhancing comprehension for code review, documentation, and technical support processes.

Files-DB

Discover an advanced semantic code search solution through a dedicated local vector database system. Benefit from seamless setup, live file tracking, and progressive indexing for improved codebase exploration.

Qdrant Vector Database

Discover a cutting-edge vector repository designed for efficient organization and retrieval of code snippets. Utilizing Docker containers and advanced sentence-transformers embeddings, this solution revolutionizes semantic search capabilities.