Deep Research From Scratch — Development skill for Claude Code

🧱 Deep Research From Scratch

Deep research has broken out as one of the most popular agent applications. [OpenAI](https://openai.com/index/introducing-deep-research/), [Anthropic](https://www.anthropic.com/engineering/built-multi-agent-research-system), [Perplexity](https://www.perplexity.ai/hub/blog/introducing-perplexity-deep-research), and [Google](https://gemini.google/overview/deep-research/?hl=en) all have deep research products that produce comprehensive reports using [various sources](https://www.anthropic.com/news/research) of context. There are also many [open](https://huggingface.co/blog/open-deep-research) [source](https://github.com/google-gemini/gemini-fullstack-langgraph-quickstart) implementations. We built an [open deep researcher](https://github.com/langchain-ai/open_deep_research) that is simple and configurable, allowing users to bring their own models, search tools, and MCP servers. In this repo, we'll build a deep researcher from scratch! Here is a map of the major pieces that we will build:


🚀 Quickstart

Prerequisites

• Node.js and npx (required for MCP server in notebook 3):

# Install Node.js (includes npx)
# On macOS with Homebrew:
brew install node

# On Ubuntu/Debian:
curl -fsSL https://deb.nodesource.com/setup_lts.x | sudo -E bash -
sudo apt-get install -y nodejs

# Verify installation:
node --version
npx --version

• Ensure you're using Python 3.11 or later.
• This version is required for optimal compatibility with LangGraph.

python3 --version

• uv package manager

curl -LsSf https://astral.sh/uv/install.sh | sh
# Update PATH to use the new uv version
export PATH="/Users/$USER/.local/bin:$PATH"

Installation

1. Clone the repository:

git clone https://github.com/langchain-ai/deep_research_from_scratch
cd deep_research_from_scratch

1. Install the