"Transcribing Voice Conversations into Structured Meeting Notes" matching MCP servers:

Enables bioinformatics analysis through natural language conversations with Claude Desktop, automatically generating and executing Python scripts to produce HTML reports and visualizations.

A unified biomedical graph database that integrates 50+ primary data sources — genes, proteins, compounds, diseases, pathways, and clinical data — into a single queryable graph with billions of cross-reference edges. Its native MCP server gives LLMs direct access to structured, authoritative biomedical data, complementing their reasoning with reliable identifiers and up-to-date database content.

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

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 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 LLM agents to search biomedical literature, retrieve article details, find related papers, manage caching, and download open-access full texts through MCP with structured, agent-friendly responses.

Integrates AlphaFold DB and eight other biomedical data sources into MCP tools for variant clinical reporting, disease-target analysis, structural intelligence, and drug repurposing, with results persisted to a local SQLite knowledge graph.

Converts natural language queries into Cypher queries against the NASA GeneLab Knowledge Graph, enabling AI-assisted analysis of spaceflight experiments and their biological effects.

Enables AI-driven pharmacogenomic analysis by querying structured genetic variant, drug response, and disease risk data. Supports natural language questions about medications, traits, and health risks based on user genome data, with privacy-first local execution.

Converts messy metabolite names into standard database identifiers (KEGG, HMDB, ChEBI, PubChem, InChIKey) and performs crosswalking to Mouse-GEM for metabolic model input, with deterministic tools and an LLM reasoning layer for identity disambiguation.

Provides LLMs with structured access to critical biomedical databases including PubTator3 (PubMed/PMC), ClinicalTrials.gov, and MyVariant.info through the Model Context Protocol.

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.

Enables protein structure and sequence searches using FoldSeek, with support for multiple databases, automatic model downloads, and structured job management.

Provides access to BioThings.io APIs for comprehensive gene and variant annotations, enabling seamless integration of biological data into workflows.

Enables AI agents to query the fission yeast PomBase database for gene summaries, GO annotations, phenotypes, orthologs, domains, and interactions via structured API calls.

Enables querying relationships between plant species, small molecules, and mitochondrial Complex I inhibitors by bridging natural-product, biodiversity, and PubMed datasets. Allows LLMs to perform structured searches and reasoning over biological data to identify potential plant-derived mitochondrial inhibitors.

Enables RNA structure analysis, sequence evaluation, and inverse design using geometric deep learning models. Supports both quick computational analysis and long-running batch processing for generating RNA sequences that fold into target structures.