Research Tools

Everything you need to measure cognitive coherence in AI models and human EEG. All tools are free for personal use.

Python SDK

pip install aime-loc          # Core (AI model scanning)
pip install aime-loc[eeg]     # + EEG support
pip install aime-loc[viz]     # + Visualization
pip install aime-loc[all]     # Everything

Scan any HuggingFace model, score EEG recordings, compare cognitive profiles, generate publication-ready figures. Full sync and async clients with automatic retry and error handling.

Full Documentation →

REST API

For any language or platform. Send JSON, receive cognitive profiles.

Endpoint	Description
POST /v1/scan	Scan an LLM for cognitive coherence
POST /v1/compare	Compare two model profiles
POST /v1/benchmark	Batch benchmark multiple models
GET /v1/leaderboard	Public TC leaderboard
POST /v1/eeg/score	Score EEG PSD epochs
POST /v1/eeg/batch	Batch EEG scoring

Authentication

curl -X POST https://api.aimindengine.com/v1/scan \
  -H "Authorization: Bearer sk-aime-..." \
  -H "Content-Type: application/json" \
  -d '{"model_id": "meta-llama/Llama-3.3-70B-Instruct"}'

Get an API Key →

MCP Server

The Model Context Protocol server lets AI agents (Claude, GPT, etc.) scan models and compare cognitive profiles autonomously. Install and connect in one command:

pip install aime-loc[mcp]
aime-loc-mcp

Available tools: scan_model, compare_models, get_leaderboard, training_audit, health_check

MCP Integration Guide →