"A Python library for visualizing neural networks" matching MCP servers:

Enables genomic sequence analysis through the Evo 2 model, supporting DNA sequence scoring, embedding, generation, and variant effect prediction with multiple model checkpoints (7B, 40B, 1B parameters).

An MCP server for querying the KEGG bioinformatics database, providing tools, resource templates, and guided prompts for pathways, genes, compounds, and more.

Enables variant annotation and effect prediction using the Ensembl VEP API, with support for batch and single queries.

This server enables multi-agent conversations for interacting with Cirro's biological data platform through its OpenAPI interface, auto-generated using AG2's MCP builder.

Enables analysis of bulk RNA-seq data using natural language queries, executing R and Python in a Docker container with automatic sample anonymization and privacy controls.

An MCP server that provides tools for searching and fetching protein data from the UniProt database using the unipressed library.

Enables bioinformatics analysis through natural language conversations with Claude Desktop, automatically generating and executing Python scripts to produce HTML reports and visualizations.

Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.

A framework that integrates Brain-Computer Interface technology with the Model Context Protocol to enable real-time neural signal processing and AI-powered interactions for healthcare, accessibility, and research applications.

Provides access to the STRING protein-protein interaction database for mapping identifiers, retrieving interaction networks, and performing functional enrichment analysis. It enables users to explore protein partners, pathways, and cross-species homology through natural language interactions.

A Model Context Protocol server that provides tools for interacting with the STRING database to analyze protein-protein interaction networks and functional enrichment. It enables users to map protein identifiers, retrieve interaction data, and generate biological network visualizations through natural language interfaces.

Predicts CRISPR gene dependencies and drug targets by integrating literature, regulatory/PPI networks, and genome-scale metabolic models.

An embedded MCP server for Cytoscape Desktop that lets AI agents load networks, set active views, and control the desktop application over HTTP.

Enables building and analyzing signalling networks from interaction databases through a Model Context Protocol server.

An MCP server for running local LLMs using llama-cpp-python, with built-in tools for generating drug-like molecule SMILES.

Enables AI agents to read and manipulate networks, tables, visual styles, and more in a live Cytoscape Web session through natural language, by connecting over Chrome DevTools Protocol.

Provides a natural language interface for scRNA-Seq analysis using the Scanpy library, supporting operations such as data preprocessing, clustering, and visualization. It enables AI agents and clients to perform complex single-cell transcriptomics workflows through the Model Context Protocol.

Provides GPU-accelerated scientific computing capabilities including symbolic mathematics, quantum wave mechanics simulations, molecular dynamics, and neural network training through four specialized MCP servers.

MCP server for STRING-DB that enables querying protein-protein interaction networks, functional enrichment, and homology mappings.

An MCP server that wraps R scripts for microbiome and amplicon (16S/ITS) analysis, providing tools for alpha/beta diversity, differential abundance, networks, and more, with PNG/PDF outputs.