"Target" matching MCP servers:

Enables automated assessment of research manuscripts against the TARGET reporting guideline for target trial emulation, providing item-by-item scoring with evidence and provenance.

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

Answers "sales dropped since last week — where?" by comparing a target period against a weekday-adjusted baseline and localizing which attribute combinations (e.g. channel=web, or Tuesday nights) explain the shift. Runs fully offline on your own CSV — no API key, no ML training, read-only.

MCP server for HumanPen that lets AI agents work on real documents (.docx, .pptx, .pdf) — humanizing content to lower AI-detection scores, converting citations, condensing, and translating while preserving formatting, tables, images, and citations.

Enables AI assistants to rapidly gather and synthesize structural, chemical, conservation, and literature data about protein binding pockets for drug-target triage. Useful as a reconnaissance step before computational binder design.

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.

Provides hackathon intelligence for builders by analyzing projects to rank best hackathons, target tracks, and differentiate using fit scoring and public gallery intel.

Enables MCP clients to drive local Codex on a target Git repository: inspect repo state, start and follow up on tasks, review events and diffs, and record audit evidence for research governance.

Enables reproducible target-disease evidence dossier assembly and validation by replaying frozen Open Targets GraphQL responses and checking citations and structured assertions against deterministic scientific contracts.

Enables querying the NASA MAST archive of space telescopes for astronomical data, including cone searches, mission-specific queries, and target name resolution.

Enables querying disease/target/drug knowledge graph from Open Targets, supporting searches, profiles, and associations via natural language through the Pipeworx gateway.

Lets agents put a five-second question to fifty verified real people and get the split back, with tools to estimate cost and timing before spending, ask and cancel questions, add more heads, page through individual answers, target audiences and countries, and export results as CSV, PDF, or PNG.

Enables access to Intrinio's premium financial data through MCP tools for options chains, unusual options activity, analyst estimates, and target prices.

Enables AI clients to perform hydraulic cone crusher selection and crushing-plant design from a requirement form and target capacity, including staged configuration, cavity/CSS/capacity checks, liner life, particle-size simulation, circulating load, and calibration against measured sieve data. It also identifies missing customer inputs and generates proposal-ready assumptions and warnings.

Enables querying today's US stock analyst upgrades, downgrades, initiations, and price-target changes, as well as consensus ratings and covering brokerages for any US ticker.

A Model Context Protocol (MCP) server that exposes ChEMBL's public bioactivity database as tools for searching compounds, retrieving bioactivity data, target compounds, and ADMET properties, usable by Claude and ChatGPT.

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.

Enables reverse DCF/FCFF valuations, solving for required margins, growth, or reinvestment to achieve a target enterprise value, with forward DCF, consistency validation, feasibility grids, and automated evals.

Superhuman data-driven science. Allows agents to upload any tabular dataset, specify a target column, and get validated predictive patterns (with p-values, effect sizes, and context from literature) that surface feature interactions and subgroup effects you'd otherwise miss. Many discoveries already made, free for open data!

An MCP server implementing the ROBINS-I V2 framework for risk-of-bias assessment in non-randomized studies, with deterministic algorithms and full provenance. It enables users to parse study documents, specify target trial results, answer signalling questions with evidence-bound quotes, and compute or override domain judgements.