CodeRAG

About CodeRAG

CodeRAG is an AI-powered tool for real-time codebase querying and augmentation using OpenAI and vector search.

ai ai-assistant ai-code ai-tools code-search faiss openai-gpt rag retrieval-augmented-generation vector

Quick Facts

Stars	185
Forks	32
Language	Python
Category	Agent Tool
Quality Score	36.75/100
Last Updated	2025-09-18
Created	2024-09-08
Platforms	python
Est. Tokens	~4k

Compatible Skills

These tools work well together with CodeRAG for enhanced workflows:

RAGLight — semantic(0.35)+complementary+rare_topics+same_lang+similar_pop+shared_platform (66%)
local_faiss_mcp — semantic(0.30)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
snippy — semantic(0.25)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (62%)
mcp-memory-service — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)

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Frequently Asked Questions

What is CodeRAG?

CodeRAG is CodeRAG is an AI-powered tool for real-time codebase querying and augmentation using OpenAI and vector search.. It is categorized as a Agent Tool with 185 GitHub stars.

What programming language is CodeRAG written in?

CodeRAG is primarily written in Python. It covers topics such as ai, ai-assistant, ai-code.

How do I install or use CodeRAG?

You can find installation instructions and usage details in the CodeRAG GitHub repository at github.com/Neverdecel/CodeRAG. The project has 185 stars and 32 forks, indicating an active community.

View on GitHub → Browse Agent Tool tools