"Using Google Search to Generate a Report" matching MCP servers:

Enables searching for academic papers and preprints across multiple platforms including Semantic Scholar, arXiv, PubMed, and CrossRef. It provides access to research records, DOI lookups, and journal metadata through a unified interface deployed on Cloudflare Workers.

Server to search PubMed (PubMed is a free, online database that allows users to search for biomedical and life sciences literature). I have created on a day MCP came out but was on vacation, I saw someone post similar server in your DB, but figured to post mine.

Enables search and retrieval of academic papers from PubMed database with advanced features like MeSH term lookup, publication statistics, and PICO-based evidence search.

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.

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.

Leverages large language models to analyze users' WeGene genetic testing reports, providing access to report data via custom URI schemes and enabling profile and report management through OAuth authentication and API utilization.

Enables users to generate volcano plots by submitting jobs with input files and parameters, supporting local or Docker execution.

Enables AI agents to search, filter, download files, and generate reports from the IGVF Data Portal using natural language commands.

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 agents to search public cancer genomics studies (TCGA, CPTAC, MSK, and more), fetch full details for individual studies, resolve gene symbols to Entrez ids, and list cancer types. Works keylessly against open cBioPortal data over a hosted MCP endpoint, a local stdio server, or plain HTTP.

Analyzes a consumer raw DNA file (AncestryDNA, 23andMe, MyHeritage, FTDNA, LivingDNA, VCF) entirely on the user's machine: Y and mtDNA haplogroups, traits, ClinVar scan, PharmCAT pharmacogenomics, and a plain-language report. Tools: analyze, summary, section, lookup, narrative_prompt/set_narrative, clinvar_findings, pharmacogenomics. Nothing is uploaded.

🔍 Enable AI assistants to search, access, and analyze PubMed articles through a simple MCP interface.

Runs the full HyphAeon report and per-pillar analyses in-process, with MEME concordance, over stdio or streamable HTTP.

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

MCP server for RNA-seq downstream analysis, wrapping R scripts to generate plots and perform analyses like PCA, volcano, heatmap, enrichment, and WGCNA.

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

🔍 Enable AI assistants to search and access bioRxiv papers through a simple MCP interface. The bioRxiv MCP Server provides a bridge between AI assistants and bioRxiv's preprint repository through the Model Context Protocol (MCP). It allows AI models to search for biology preprints and access their

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.

Grounds gene-nomenclature work in the HUGO Gene Nomenclature Committee (HGNC) dataset, enabling resolution of gene symbols and IDs to canonical HGNC identifiers, plus cross-references and batch operations.

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.

Enables AI agents to retrieve cited pharmacogenomic and gene-variant information, including drug–gene guidance from CPIC/DPWG and rsID lookups, so responses can quote curated sources instead of relying on memory. A local package also lets users read raw DNA files on their own computer without sending the file data to the remote service.

Enables coding agents to interact with the Reactome pathway database, including search, lookup, hierarchy traversal, SBML/SBGN export, and gene-set enrichment 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.

Provides read-only access to the ProPaths verified protein interactome, letting AI agents search proteins, retrieve mechanistic interaction details, and explore pathway ontology through MCP tools, resources, and prompts.

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.