CLI and MCP server for mechanistic interpretability: trace which attention heads and neurons drive an LLM's output, built on TransformerLens. Schema-versioned JSON output, agent-callable via MCP, activation patching, zero-ablation, circuit sketches for GPT-2, Llama, Gemma, Qwen, Pythia and 240+ open-weight models.
Ask a language model "why did you say that" and get back the actual attention heads and neurons responsible, as JSON, from the command line or from an agent over MCP. Not on PyPI yet, so install from source: ```bash git clone https://github.com/RudrenduPaul/NeuronScope cd NeuronScope pip install -e .