"Using Google Sheets as a CRM" matching MCP servers:

Enables AI-powered genomic variant analysis including variant impact prediction, regulatory element discovery, and batch variant scoring. Currently operates in mock mode as a proof-of-concept awaiting the public release of Google DeepMind's AlphaGenome API.

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

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.

Allows to retrieve information about an AnnData object via MCP using the read_lazy function from anndata.

Exposes pipen bioinformatics pipelines as MCP tools, allowing AI assistants to discover and run complex workflows through a progressive disclosure interface.

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.

Enables AI agents to resolve marine species names to OBIS taxon records, retrieve georeferenced ocean occurrence records with optional date filtering, and pull aggregate statistics such as record counts, contributing datasets, and observed year ranges. Queries the Ocean Biodiversity Information System keylessly over the Pipeworx gateway or as a local stdio server.

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.

Enables LLMs to run rule-based molecular interaction simulations using the Kappa language through the Kappybara package. Returns simulation results as CSV data for analysis of biochemical systems and molecular binding dynamics.

Enables protein structure prediction using the Chai-1 model via Docker, with tools for small peptides, FASTA-based predictions, MSA-enhanced predictions, batch processing, and job management.

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.

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 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.

Provides direct SQL access to a locally hosted Reactome database, enabling schema discovery, guarded read-only queries, and ergonomic helpers over the full relational schema.

Guides researchers, including those new to BPP, from raw sequence data to a validated control file that has passed a short test run. Wraps BPP command-line tools without running long analyses itself.

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.

A Model Context Protocol server that interfaces with Biomart databases, allowing models to discover biological datasets, explore attributes/filters, retrieve biological data, and translate between different biological identifiers.