"A server for bio-medical data or research using MCP" matching MCP servers:

An MCP server that enables AI assistants to generate, score, and analyze DNA sequences using the evo2 genomic foundation model. It supports multiple execution modes including local GPU, SLURM clusters, and the Nvidia NIM cloud API for tasks like variant effect prediction and sequence embedding.

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 Claude Code to interact with a TACC or SLURM HPC cluster for bioinformatics pipelines, allowing job management, log reading, file browsing, remote script execution, and job submission through natural language.

Exposes over 100 deterministic medical research engines to any MCP-capable agent, covering statistical tests, survival analysis, bioinformatics pipelines, primer/sequence design, modeling, and PubMed literature search. Every response is computed with real algorithms and tagged with an engine_status of real, unavailable, or error, so agents never receive fabricated numbers.

Enables in-chat scientific viewers for molecular structures, sequence alignments, and slide images, plus data tools for searching structures, fetching sequences, aligning them, and drafting NGS analysis plans.

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 workflow management and Docker image building for Bio-OS platform. Supports WDL workflow submission, validation, and monitoring, along with Docker image building and status tracking for bioinformatics workflows.

Enables AI assistants to perform DNA/RNA sequence alignment using BWA (Burrows-Wheeler Aligner), supporting both short and long read alignment to reference genomes with indexing, BWA-MEM, and BWA-backtrack algorithms.

BioMCP is an open-source MCP server that connects any AI assistant to 15 open bioinformatics databases with zero configuration. It provides 23 tools for literature, sequences, BLAST, structures, enrichment, annotations, genomes, interactions, variants, domains, compounds, and single-cell data.

A Model Context Protocol server that enhances language models with protein structure analysis capabilities, enabling detailed active site analysis and disease-related protein searches through established protein databases.

Enables AI agents to retrieve and analyze breeding data from BrAPI-compliant databases through shared tools, with human-in-the-loop approval and verification.

Retrieve genomic data from EGA, ENA, ENCODE, GEO and NCBI, read bounded regions from indexed BAM/CRAM, VCF and bigWig files, and query source-attributed reference evidence. Runs locally with 23 MCP tools. MIT-licensed; research use.

Enables MCP-compatible AI assistants to look up clinical variants and batch-annotate NGS spreadsheet outputs via ClinVar, gnomAD, and VarSome. Provides tools for variant lookup, Excel inspection, and folder-level batch processing.

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 AI agents to resolve and cross-reference biological entities such as genes, proteins, and aliases across authoritative databases like HGNC, NCBI Entrez, and UniProt, with confidence scores and source citations.

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

Parses MS-DIAL binary lipidomics outputs and runs standard analyses server-side, returning compact summaries so an LLM can drive full lipidomics analysis without exposing raw matrices.

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.

Biological and medical data search MCP server.

A bridge connecting AI agents to NCBI's PubMed database through the Model Context Protocol, enabling seamless searching, retrieval, and analysis of biomedical literature and data.

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

Connects 3D Slicer with AI assistants through the Model Context Protocol, enabling medical image processing and scene manipulation using natural language.

A stateless, deterministic Bio-Robotics Core Engine converting biological data (UniProt API) to G-code.

Read-only access to a curated, evidence-labelled corpus of mTOR research: studies, entities, signed pathway relations with supporting and conflicting evidence, and open questions.

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 the generation, mutation, and evolution of DNA and protein sequences using various evolutionary models and phylogenetic algorithms. It supports realistic next-generation sequencing read simulation and population-level evolutionary tracking for bioinformatics research and testing.

A bioinformatics MCP server that connects AI clients to over 30 life science databases and 32 curated tools for research, drug discovery, and clinical analysis.

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 standardized access to aging and longevity research data from the OpenGenes database, enabling AI assistants to query comprehensive biomedical datasets through SQL and structured interfaces.