"Understanding Inference Models" matching MCP servers:

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.

A structure-aware MCP server for querying the SPOKE biomedical knowledge graph, enabling entity resolution, schema introspection, path finding, and safe Cypher queries for biomedical knowledge inference.

Phylogenetic inference server driving IQ-TREE 2, always returning per-clade bootstrap support plus model selection, tree comparison, and alignment simulation, with detailed diagnostics like conflicting clades and model uncertainty.

An MCP server that provides direct access to PubMed and PubMed Central via the NCBI E-utilities API. It enables AI models to search biomedical literature, retrieve detailed article metadata, and download open-access full texts.

An MCP server that provides mouse genetics data from Mouse Genome Informatics (MGI), enabling LLM agents to query markers, mutations, alleles, phenotypes, and disease models.

Enables editing and querying of Gene Ontology Causal Activity Models (GO-CAMs) through the Barista API. Supports model creation, individual and fact management, evidence addition, and causal pathway construction for biological knowledge representation.

Enables read-only interaction with DHIS2 health data by searching indicators and querying compact analytics results, designed for small local models.

Exposes NeuroGraph's scientific API to AI models as MCP tools, enabling them to query, analyze, and visualize brain networks — regions, tracts, connectivity, literature, and cross-species homologies — drawn from a portable SSD-based neuroimaging data library. Lets models read real atlas data, load datasets, compute graph metrics, and produce visualization scene descriptors without acting as the scientific engine itself.

Enables design-correct, conversational analysis of NHANES public-use data by automating file discovery, merging, weight selection, pooling, survey variance estimation, and mortality-linked Cox models.

An MCP server for NONMEM pharmacometric modeling that provides structured access to model parsing, execution, and results analysis. It enables users to perform diagnostics, manage PsN workflows, and translate models to mrgsolve for PK simulations through natural language.

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.

Enables language models to query a clinical relational database through a small set of validated, row-capped tools, with evaluation of answerability and data leakage.

Enables wing simulation and aerodynamic analysis for pterosaur-inspired flight models. Provides lift, drag, and thrust calculations through the pterasim module with analytical fallbacks when the native module is unavailable.

Enables LLM agents to programmatically inspect hardware resources, run in-memory inference benchmarks, list supported fMRI studies, and retrieve cortical and subcortical atlas region indices via JSON-RPC 2.0.

Predicts CRISPR gene dependencies and drug targets by integrating literature, regulatory/PPI networks, and genome-scale metabolic models.

An MCP server that provides a toolbox for interacting with EPA SWMM stormwater models, enabling users to analyze model data and interpret results through LLM-driven tools. It assists stormwater modelers in understanding hydraulic systems and modeling behavior using natural language interfaces.

Enables compiling typed decision queries into the smallest decision-sufficient evidence context with machine-checkable Context Certificates, providing auditable executable-biology inference through local MCP tools.

Provides MCP tools for edge-based pharmaceutical shipment disposition decisions, returning release, review, or quarantine outcomes while recording every decision in a tamper-evident, hash-chained audit trail.

Enables AI coding agents to perform end-to-end medical image analysis locally, from inspecting CT/MRI/X-ray studies and running containerized segmentation models like MedSAM2, TotalSegmentator, and HD-BET to refining masks, measuring volumes, and writing reports. It pairs preset or custom guideline protocols with a code-customizable viewer that renders images back to agents as annotated PNGs and to humans as interactive HTML.

Provides AI-powered medical image analysis tools for LLM agents, enabling tasks such as X-ray classification, interactive segmentation, and visual question answering. It supports multi-step diagnostic reasoning and clinical workflows through a suite of specialized medical AI models.