"PyTorch-related MCP (Model Context Protocol) implementation or server" matching MCP servers:

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.

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.

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.

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.

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

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

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.

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

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

Enables AI agents to operate DSpace repositories through a typed interface, including SAF package building, metadata editing, scientometric harvesting, open-access PDF downloads, and repository administration.

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.

A comprehensive Model Context Protocol (MCP) server providing advanced access to the ChEMBL chemical database.

A Model Context Protocol (MCP) server that provides statistical analysis tools for sales and salary data.

Provides access to Agent Observatory's live experiment data, including visit stats, AI crawler info, and self-classification endpoints. Enables AI agents to discover and interact with the observatory's passive research infrastructure.

A Model Context Protocol server for scholarly tools, enabling AI assistants to interact with scholarly data and services via discoverable tools.

An MCP server that provides controlled read/write tools for managing local-first research memory in an Obsidian vault, enabling AI agents to maintain project context across sessions.

A Model Context Protocol (MCP) server implementation that provides the LLM an interface for visualizing data using Vega-Lite syntax.

A standalone Model Context Protocol (MCP) server that enables AI assistants to interact with the cTrader trading platform.