"Gin web framework for Go programming language" matching MCP servers:

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 editing and querying of Gene Ontology Causal Activity Models (GO-CAMs) through the Barista API. Supports model creation, individual and fact management, evidence addition, and causal pathway construction for biological knowledge representation.

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.

Enables searching a manually curated database of stable macromolecular protein complexes by protein or complex name, gene, GO term, or biological process, and fetching individual records by accession to retrieve subunits with UniProt identifiers, biological roles, and stoichiometry. Complements UniProt, IntAct, and STRING, and can be used keyless over a hosted gateway endpoint or run locally over stdio.

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.

Enables AI agents to query the fission yeast PomBase database for gene summaries, GO annotations, phenotypes, orthologs, domains, and interactions via structured API calls.

Enables AI agents to browse the Gene Ontology through the EBI QuickGO API, including keyword search for GO terms, retrieval of a term's name, aspect, definition and synonyms by id, and listing the GO annotations tied to a UniProt accession. Runs keyless over HTTP or as a local stdio server, with an optional gateway route that lets plain-English questions be answered without choosing tools manually.

A specialized MCP server for Metal-Organic Framework research that provides tools for database searching, structural optimization, and energy calculations via ASE. It enables scientific workflows by allowing users to interact with MOF data and perform chemical simulations through a standard SSE interface.

Enables AI assistants to query VCF files through MCP tools that summarize variants, identify pathogenic and carrier variants, interpret pharmacogenomic results, and determine APOE status, with web app and Claude Desktop support.

Provides a natural language interface for single-cell RNA-Seq analysis using the decoupleR framework. It enables users to perform biological pathway inference, data clustering, and visualization through MCP-compatible AI clients.

Provides a natural language interface for inferring Copy Number Variations (CNVs) from scRNA-Seq data using the infercnvpy framework. It enables users to perform data preprocessing, CNV inference, and visualization through chromosome heatmaps, UMAP, and t-SNE plots.

Framework for building bioengineering automation tools that AI assistants can call via the Model Context Protocol, handling server registration and tool discovery automatically.

An MCP server that grounds protein research in the UniProt SPARQL endpoint, providing tools for querying proteins, sequences, variants, diseases, and more via intent-named tools and raw SPARQL.

Enables language models to search biomedical literature, fetch sequences, and follow links across Entrez databases through eleven read-only tools wrapping the nine NCBI Entrez E-utilities. It handles URL building, pacing, redirects, response caps, and API-key redaction so queries can be answered without a browser or scraping.

Enables AI assistants to clean PDB structures and run initial-stage energy relaxation for biomolecular modeling. It provides a structured workflow for preparing structures before production molecular dynamics or coarse-graining pipelines.

MCP server that provides tools to query harmonized gene-disease validity data from the Gene Curation Coalition, supporting consensus and conflict detection for gene-disease assertions.

Enables DNA sequence analysis and variant effect prediction using Evo2-7B via MCP tools, providing forward inference, likelihood scoring, and batch variant comparison through natural language.

MCP server exposing REINVENT4 generative molecular-design operations as validated, LLM-callable tools for drug discovery, including sampling, transfer learning, reinforcement learning, and molecular analysis.

A Model Context Protocol (MCP) server for interacting with Gen3 data commons, with GraphQL query validation to reduce hallucinations.

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.