AgentIndex icon
AgentIndex
GPT Researcher logo
GPT Researcher
★ 30.2k
vs
code-graph-rag logo
code-graph-rag
★ 5.3k

GPT Researcher vs code-graph-rag

GPT Researcher: GPT Researcher is an open-source LLM agent designed for deep, structured research on any topic using web and local sources. It produces detailed reports with citations by running parallel research agents, scraping relevant sources, filtering content, and synthesizing findings. Supports local document research, customizable report formats, and multiple LLM backends including OpenAI, Anthropic, and Ollama.; code-graph-rag: Code-Graph-RAG is an accurate Retrieval-Augmented Generation (RAG) system designed for multi-language codebases. It uses Tree-sitter to analyze code, build comprehensive knowledge graphs, and allows natural language querying of codebase structure and relationships. The system also includes advanced editing capabilities, enabling users to modify code directly through natural language prompts.

01

TL;DR

GPT Researcher logo
GPT ResearcherRAG / Knowledge Base · ★ 30.2k
When to choose:
  • You want an Apache-2.0 agent that plans sub-questions, searches the web and local documents in parallel, and writes 2,000+ word reports with citations.
  • You want to use it as a Python library, standalone web app, or MCP-connected research skill with PDF/Word export.
When to skip:
  • You want a general-purpose super-agent harness with a bash sandbox, persistent memory, and Feishu/WeCom/Slack bots; DeerFlow is built for that.
  • You do not want per-report search API (e.g. Tavily) and multi-call LLM token costs.
Read GPT Researcher full review →
code-graph-rag logo
code-graph-ragRAG / Knowledge Base · ★ 5.3k
When to choose:
  • You want to parse a multi-language monorepo with Tree-sitter into a Memgraph knowledge graph and query or edit it via natural language or Claude Code MCP.
  • You want semantic code search using UniXcoder embeddings paired with Cypher graph queries.
When to skip:
  • You want RAG over PDFs, Word files, and slides rather than source code repositories; use RAGFlow or MaxKB.
  • You want a zero-dependency code context MCP server without running Docker and Memgraph; jCodeMunch or Context7 are much lighter.
Read code-graph-rag full review →
02

Side-by-Side Comparison

Field
GPT Researcher logoGPT Researcher
code-graph-rag logocode-graph-rag
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 30.2k
★ 5.3k
License
Apache-2.0
MIT
Install Command
pip install gpt-researcher
git clone https://github.com/vitali87/code-graph-rag.git && cd code-graph-rag && uv sync --extra treesitter-full && cp .env.example .env && docker-compose up -d
Updated
1w ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Agent, Deep Research, Web Scraping
ai, ast, claude-code
03

Features

GPT Researcher logoGPT Researcher
01Parallel research agents scraping and synthesizing multiple web sources simultaneously
02Generates structured reports with citations in Markdown, PDF, or Word format
03Supports local document research in addition to web search
04Customizable report types: research reports, outlines, resource lists, and more
05Compatible with OpenAI, Anthropic, Groq, Ollama, and other LLM providers
code-graph-rag logocode-graph-rag
01Multi-Language Support
02Tree-sitter Parsing
03Knowledge Graph Storage
04Natural Language Querying
05Advanced File Editing
04

Use Cases

GPT Researcher logoGPT Researcher
↳Automating deep research reports on any topic with sourced citations
↳Conducting market research, competitive analysis, or literature reviews at scale
↳Building research pipelines that combine web search with local knowledge base retrieval
code-graph-rag logocode-graph-rag
↳Analyze and ingest multi-language codebases into a knowledge graph.
↳Query codebase structure and relationships using natural language.
↳Receive AI-powered optimization suggestions and perform surgical code edits.
05

Best For

GPT Researcher logoGPT Researcher
Most PopularEssentialTrending
code-graph-rag logocode-graph-rag
—
FAQ

FAQ

What is the difference between GPT Researcher and code-graph-rag?
Both GPT Researcher and code-graph-rag are in the RAG / Knowledge Base category. GPT Researcher has 30.2k stars, while code-graph-rag has 5.3k stars.
Which is better, GPT Researcher or code-graph-rag?
The best choice depends on your use case. Choose GPT Researcher if Automating deep research reports on any topic with sourced citations, and code-graph-rag if Analyze and ingest multi-language codebases into a knowledge graph..
Is GPT Researcher free or open source?
Yes, GPT Researcher is open source on GitHub (Apache-2.0).
Is code-graph-rag free or open source?
Yes, code-graph-rag is open source on GitHub (MIT).
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