"AWS cloud service monitoring" matching MCP servers:

Bridge any AI coding assistant directly to GenePattern — run bioinformatics modules, manage cloud jobs, and stream results, all through natural language.

Enables AI clients to connect to Galaxy instances, inspect histories and reports, discover tools and workflows, submit analyses, and monitor their results via interactive cards.

Wraps NCBI BLAST+ blastp into a FastMCP service for auditable protein homology searches with local output artifacts and structured metadata.

Provides protein family, domain, and functional annotation using InterProScan, supporting local or API backends.

Enables AI-powered protein structure prediction and variant analysis via Docker, with tools for submitting predictions, batch processing variants, and monitoring jobs.

Enables workflow management and Docker image building for Bio-OS platform. Supports WDL workflow submission, validation, and monitoring, along with Docker image building and status tracking for bioinformatics workflows.

Enables querying of per-residue missense tolerance, Pfam domain annotations, and variant counts for human transcripts by wrapping the MetaDome web service. Provides MCP tools for resolving transcripts, requesting tolerance landscapes, and identifying constrained regions.

An MCP server that enables AI assistants to generate, score, and analyze DNA sequences using the evo2 genomic foundation model. It supports multiple execution modes including local GPU, SLURM clusters, and the Nvidia NIM cloud API for tasks like variant effect prediction and sequence embedding.

Enables querying and browsing ontologies from the EBI Ontology Lookup Service, including searching for terms, retrieving term details, and navigating ontology hierarchies via natural language.

Enables AI assistants to create, monitor, and manage computational tasks through GA4GH Task Execution Service (TES) functionality. Provides seamless access to TES-compliant services for executing bioinformatics and scientific computing workflows.

Enables protein stability prediction ($DeltaDelta$G and $Delta$Tm) and systematic mutation analysis using the SPIRED-Stab deep learning model. It supports single variant analysis, batch processing, and job monitoring via Docker-based inference.

Enables protein sequence analysis and structure prediction by extracting ESM-2 embeddings and batch processing FASTA files via Docker. It provides tools for large-scale embedding extraction, job monitoring, and model management within an MCP-compatible environment.