"A tool for following and completing a plan step by step" matching MCP servers:

Provides an MCP interface to the ROBOT command-line tool for OWL ontology editing, enabling operations like merging, reasoning, and conversion via natural language.

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).

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.

Provides access to EMBL-EBI bioinformatics data including InterPro domains, Pfam families, protein features, and taxonomy through a unified tool.

MCP server for querying the GWAS Catalog (EBI/NHGRI), a curated catalog of genome-wide association studies. It enables AI agents to search and retrieve study data via natural language or direct tool calls.

Enables AI assistants to rapidly gather and synthesize structural, chemical, conservation, and literature data about protein binding pockets for drug-target triage. Useful as a reconnaissance step before computational binder design.

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 querying of the Monarch Initiative biomedical knowledge graph for genes, diseases, phenotypes, and their associations through natural language or direct tool calls.

Annotate variants by with a deep and rich set of data. Can annotate: genetic change, rsID, CAid, HGVS (g./c./p.), protein change.

Federates 13 gene-related MCP backends (gnomAD, GTEx, etc.) behind a single Streamable HTTP endpoint with collision-free namespacing and search-based tool discovery.

Validates the physical and chemical plausibility of ligand–protein docking poses using the PoseBusters tool.

Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.

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 explore VEuPathDB WDK catalogs, searches, parameters, and gene data, and to perform gene lookups, expression summaries, step estimates, and download URL retrieval using VEuPathDB credentials.

An MCP server that enables scRNA-Seq analysis through natural language, providing tools for data preprocessing, clustering, and biological visualization. It supports both predefined function execution and a flexible code mode powered by a Jupyter backend for automated single-cell transcriptomics workflows.

MCP server for querying the EBI PRIDE Archive, a proteomics (mass-spectrometry) data repository, through natural language or direct tool calls.

A terminal-based bioinformatics CLI chat tool that integrates Ensembl VEP, NCBI ClinVar, an MCP server layer, and OpenRouter's NVIDIA Nemotron 3 Ultra model to provide variant consequence and clinical significance lookups with clear summaries in a Rich-powered CLI.

A self-driving cheminformatics MCP server that dynamically exposes a growing library of RDKit-based molecular analysis tools (fingerprints, descriptors, substructure matching, drug-likeness filters, and more) as MCP tools, with each skill autonomously implemented and tested by an agent loop without human intervention.

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