"Factur-X MCP (Model Context Protocol) Integration" matching MCP servers:

An MCP server that integrates AI retrievals with NASA's Common Metadata Repository (CMR), allowing users to search NASA's catalog of Earth science datasets through natural language queries.

A Python implementation of the Model Context Protocol (MCP) server that enables searching and extracting information from arXiv papers, designed to be extensible with additional MCP tools.

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.

Access to many public datasets right from your LLM application.

Enables read-only research on public X data through tools for posts, threads, profiles, search, trends, collections, and saved-result analysis using free public APIs and optional sessions.

MCP server for IG's REST Trading API and Lightstreamer streaming API. Provides tools for accounts, markets, positions, orders, watchlists, sentiment, OTC trades, and streaming price/account/trade/chart data.

Enables natural language control of quantum photonics experiments through the qudi framework. Supports safe instrument control, measurement execution, and safety system management with built-in runlevel protection and parameter validation.

A read-only MCP server that lets ChatGPT use Grok's x_search to retrieve and analyze posts and threads from specified X accounts, returning Chinese research reports with source links.

Enables querying Google NotebookLM notebooks directly from Claude Desktop (MCP) and Claude Code (CLI), providing citation-backed answers from Gemini.

Provides local, evidence-aware research memory with human review, revision history, and an inspector, allowing assistants to preserve source reports, inferences, assumptions, and evidence across sessions.

Read-only X/Twitter research MCP server allowing AI assistants to search viral content, analyze accounts, track trends, and discover niche leaders without requiring the official X API.

Enables AI agents to perform corpus analysis tasks such as discovery, search, and data access via the Model Context Protocol.

Enables running the same prompt(s) across roughly 300 models from Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, Qwen and others, then comparing per-model outputs, latency, token usage, error rates and billed cost side by side. Supports free cost estimates before launching, asynchronous run creation with status polling and cancellation, prepaid x402 credit top-ups, and an optional AI-written comparison summary of the results.

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

Provides access to ancient text corpora via stdio, enabling corpus listing, status checks, searching, and text/metadata retrieval with provenance envelopes.

Provides source-grounded Christian research material with exact passages, provenance, and stable citations via a REST API.

Provides provenance-aware access to selected Sefaria Bible context, including Targumim, Mishnah, Jewish commentary, Josephus/Philo, and lexicon lookups, with on-demand caching of long-tail Sefaria texts.

Provides AI assistants with structured, authoritative knowledge of the HICAR atmospheric model, including namelist options, physics schemes, output variables, documentation, and source code.

Enables real-time queries and large-scale data collection from X (Twitter) and Reddit via the Model Context Protocol, powered by Bittensor's Data Universe.

Enables interaction with an explicit ARC-AGI-3 world model through typed operations for actor/rule editing, deterministic simulation, rendering, and observation comparison.