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Analyze proteins with embeddings, mutation scoring, scans, and structure prediction
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Axon NeuroAutomata" MCP server from askskill: Run: claude mcp add --transport http 'ai-axonagentic-neuroautomata' 'https://mcp.neuroautomata.axonagentic.ai/mcp'
Use ESM-2 or ESMC to generate embeddings for this protein sequence, and explain the output dimensions and suitable downstream tasks: MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDL.
Returns protein embeddings with a brief explanation of their use in clustering, similarity analysis, or function prediction.
Score and rank the following mutations in this protein sequence, and identify which are more likely to affect function or stability: A15V, G24D, F36Y. Original sequence: MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDL.
Provides scores for each mutation, a ranked risk list, and a brief interpretation of potential functional or stability impact.
Run a single-mutation landscape scan for this protein and use ESMFold to predict the 3D structure of the wild-type sequence; then summarize the most sensitive positions: MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDL.
Delivers single-mutation scan results, a structure prediction, and a summary of key sensitive positions.
Run AlphaFold3 protein predictions, variant batches, and job monitoring via Docker.
Turn codebases into knowledge graphs for architecture and dependency understanding.
Access PDBe to query protein structures and retrieve structural biology data.
Control PyMOL with natural language for protein structure analysis and visualization.
Analyze sequences and design molecular biology workflows for DNA, RNA, and proteins.
Query AlphaFold and biomedical sources through a local knowledge graph.