"A guide for improving AI prompt output quality" matching MCP servers:

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.

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.

An MCP server for searching and accessing RNA sequencing datasets from the European Nucleotide Archive (ENA), supporting bulk, single-cell, and spatial transcriptomics with advanced filtering and download capabilities.

MCP server for polygenic risk score analysis, wrapping just-prs to enable catalog search, PRS computation, VCF normalization, percentile and risk estimation, and quality assessment.

An MCP server that provides standardized access to biomedical knowledge bases and resources, enabling AI systems to retrieve verified information from sources like bioRxiv, EuropePMC, and various protein/gene databases.

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

Enables AI assistants to perform NCBI BLAST sequence similarity searches through natural language, supporting nucleotide and protein searches, custom database creation, and multiple output formats.

Enables AI assistants to perform quality control analysis on high-throughput sequencing data using FastQC and MultiQC. It supports single-file and batch processing of FASTQ/FASTA files and generates comprehensive, interactive summary reports.

Enables AI assistants to generate publication-quality bioinformatics visualizations (volcano plots, PCA, heatmaps, etc.) directly from raw biological data.

Resolves free-text condition and disease strings — trial-registry condition fields, drug-label indications, hand-typed wording — onto the Mondo Disease Ontology, returning the best term id and label along with a trustworthy match-quality label (exact label/synonym, broader, narrower, fuzzy, or no-match) plus cross-ontology xrefs. Optionally expands a resolved term to all of its descendant ids for building subtype-inclusive registry filters.

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 querying the BOLD Systems global DNA barcode database for specimen records, taxonomy, barcode sequences, and BIN clusters, with keyless access and FASTA-ready output.

A professional MCP server for comprehensive bioinformatics quality control, providing automated FastQC/MultiQC analysis, HTML report parsing, and advanced data visualization for sequencing data.

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

BioOpenMCP enables users to run bioinformatics tools like FastQC, Cutadapt, and STAR with background execution and status checking. It integrates with Claude Desktop to perform quality control, trimming, alignment, and reporting via natural language.

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.