"Analyzing Bitcoin Blockchain Operations" matching MCP servers:

Enables building and analyzing signalling networks from interaction databases through a Model Context Protocol server.

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.

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 an MCP interface to the ROBOT command-line tool for OWL ontology editing, enabling operations like merging, reasoning, and conversion via natural language.

Enables interaction with MGnify metagenomics resources and tools through the Model Context Protocol. Provides access to MGnify's API for querying and analyzing metagenomic datasets and related biological information.

Enables AI assistants to query genetic variant data, gene constraints, and population genetics information from the gnomAD (Genome Aggregation Database) through its GraphQL API. Supports searching for genes and variants, retrieving constraint scores, analyzing population frequencies, and accessing genomic coverage data.

Enables AI assistants to query gene annotations, expression, pathways, variants, and more via the MyGene.info API, supporting batch operations and multiple biological data sources.

Enables users to manage and navigate nf-core bioinformatics pipeline repositories, allowing list, search, and explore operations on pipeline configurations, workflows, and modules.

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.

An MCP server that provides access to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, offering 30 tools for searching and analyzing biological data like pathways, genes, and compounds. It supports integration with LangChain and Ollama to enable LLMs to interact with comprehensive genomic and chemical datasets.

Enables quantum machine learning operations using Qiskit, including executing quantum circuits, computing quantum kernels, training variational quantum classifiers, and evaluating quantum ML models.

Provides comprehensive access to the NCBI Datasets API, enabling genomic, taxonomic, and biological data operations through 31 specialized tools.