"WP Rocket" matching MCP servers:

Live space data for AI agents: upcoming rocket launches (SpaceX, NASA, Rocket Lab…), ISS pass predictions for any city or coordinates (live SGP4), and launch news in 7 languages. Read-only, no auth, no API key. Backed by gocosmik.com — the free real-time 3D satellite tracker.

MCP server for querying verified data on European private equity & venture capital firms — funds, AUM, portfolio companies, and exits — from the GP Intel database.

Enables natural language access to Japanese patent information through the JPO API, allowing users to query patent data directly from Claude Desktop or Claude Code.

Provides access to global rocket launch data, including upcoming and historical launches, launch details, space agencies, astronauts, events, and expeditions, enabling natural language queries about space activities.

An MCP server implementing the Wildlife Insights GraphQL API, providing natural language tools for wildlife management and species identification.

Enables AI assistants to query the FoxData API for iOS and Google Play app analytics, including downloads, revenue, rankings, keywords, competitor insights, and ad data across 200+ countries. Supports natural-language requests to retrieve app intelligence and market data.

Enables LLM agents to safely perform WorldQuant BRAIN research tasks such as account status checks, dataset/field/operator discovery, recent alpha retrieval, candidate writing, and guarded multi-simulation runs, while deliberately excluding alpha submission from the MCP layer.

MCP server for materials science monitoring, searching ArXiv preprints and OpenAlex articles with sovereign intelligence filtering by country.

An MCP server for Japanese literature research that provides unified search across NDL, CiNii, J-STAGE, and other Japanese academic databases, with Skills to assist in search planning and result evaluation.

Enables querying a brand's visibility in AI assistant answers, including competitor presence, tracked prompts, and the answers and sources behind the metrics.

Enables AI assistants to solve linear, nonlinear, and integer optimization models with a locally installed LINGO 11 solver and read the results back as structured data — status, objective, variable values, reduced costs, row slacks, and dual prices. It also runs arbitrary LINGO command-window analyses, reports the detected installation and license status, and lists the bundled sample models, correctly flagging infeasible or unbounded models instead of inventing an optimum.

Enables users to discover, search, validate and cross-map versioned statistical code systems — including industry, occupation, product, education and questionnaire response hierarchies — with deterministic retrieval and provenance. It supports questionnaire development, survey coding and reproducible statistical harmonisation without running any AI model inside the server.

Enables AI assistants to search and access arXiv papers through a Model Context Protocol interface, allowing for paper search, download, listing, and reading functionality.

Enables local evaluation and revision comparison of how audience attention, curiosity, surprise, understanding, fatigue and mixed emotions evolve through a creative work, based on time-ordered cue annotations rather than automatic media analysis. Also exposes audience-panel weighting, sensitivity checks, dataset inspection, calibration fitting/application and parameter tuning, all computed from supplied objects without external calls.

A tool for SHACL-based assessment, comparison, and coverage analysis of digital passport data models, designed for AI-agent orchestration.

An append-only research operations framework and read-only MCP that tracks research plans, approvals, observations, claims, failures, revisions, and contributions with source-grounded evidence, providing search, evidence fetch, and audit capabilities without direct ledger writes.

Enables MCP clients to query the Open Science Framework for public research project metadata, abstracts, and component listings using OSF project IDs or URLs.

Enables AI agents to access audited SEC intelligence, including scored catalyst picks and track record data, via the Model Context Protocol.

Enables LLM agents to perform Bayesian Maximum Entropy geostatistical analysis through natural language rather than code, supporting spatial, network, and physics-informed uncertainty modeling.

MCP server for publishing markdown AI research entries to a Convex database. Supports both development and production environments with secure deployment credentials.