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AI Toolkit
Everything you need to ship AI features: coding assistants, LangChain/LangGraph, vector stores, and the classic ML stack.
Claude Code
Github Copilot
LangChain
LangGraph
LlamaIndex
CrewAI
Dify
MCP
Ollama
LM Studio
Lovable
v0
Windsurf
Cursor
Hugging Face
Pinecone
PyTorch
Tensorflow
Project Jupyter
What’s in the pack
The AI developer stack splits into three broad tiers, and this pack covers each of them. Coding assistants: Claude Code, GitHub Copilot, Windsurf, Cursor, v0, Lovable. Orchestration & agents: LangChain, LangGraph, LlamaIndex, CrewAI, MCP, Dify. Local / infra: Ollama, LM Studio, Hugging Face, Pinecone, plus the durable ML classics (PyTorch, TensorFlow, Jupyter). Together they cover the tooling most AI-first codebases actually reach for.
How to use them
For a landing-page “we work with…” grid, group by tier rather than alphabetizing — readers parse “coding agents / orchestration / infra” faster than a flat row. In architecture diagrams, Claude and Copilot typically sit at the top (driving the IDE), LangChain/LangGraph in the middle (the agent runtime), and Pinecone/Ollama at the bottom (retrieval and inference). MCP is a protocol not a product; use its mark only when specifically referring to the protocol.
Related packs
- LLM providers pack — the models these tools call into
- Modern data stack — for the retrieval and analytics side