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2026-05-22

Ariadne's thread — a way out of the microservice maze. Local cross-service semantic chain hinter for microservices (GraphQL/HTTP/Kafka/frontend)

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Clinical research MCP server providing real-time access to PubMed (35M+ papers) and ClinicalTrials.gov (400K+ trials). Built for trial coordinators and life sciences teams. No API key required.

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全面解析MCP For ResearchMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器,MCP For Research能让AI助手访问实时数据、执行操作,为您提供更智能的工作体验和自动化解决方案。

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Enables semantic search across the Arke Institute's extensive archive of NARA records and presidential libraries using natural language queries. Provides access to millions of historical documents, photographs, and records with OCR'd content and complete metadata.

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AnchorRegistry is the open provenance layer for the agentic economy. Every digital artifact — code, research, data, models, media, agents, transactions — can be anchored to Base L2 with a permanent, machine-resolvable identifier (an AR-ID). When an AI assistant encounters an SPDX-Anchor or DAPX-Anchor tag in a README, paper, model card, or website, this MCP server lets it resolve the artifact's full provenance record in one call: who anchored it, when, what type it is, manifest hash, and whether the tree has been sealed, retracted, voided, or affirmed.\\r\\n\\r\\nThis is the verify-only edition (v0.1). Three read-only, authless tools wrap the public AnchorRegistry verify endpoints. Free, no API key, no account, no rate limit beyond defaults. Future versions will add registration, balance, and seal tools once the MCP credential pattern stabilizes.

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命令预览

npx mcp-remote https://mcp.anchorregistry.ai/mcp [object Object]

Agent-to-Agent (A2A) communication protocol for inter-agent coordination and a Model Context Protocol (MCP)-inspired architecture for interacting with external tool servers.

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Enables AI agents to save, search, and manage markdown-based research articles through a complete CRUD interface. Supports creating, reading, updating, and deleting articles with frontmatter metadata in a self-hosted file-based system.

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Enables multi-source literature search, full-text retrieval, reference analysis, and journal quality assessment across Europe PMC, PubMed, arXiv, CrossRef, OpenAlex, and EasyScholar via the MCP protocol.

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全面解析Arxiv Search MCP ServerMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器,Arxiv Search MCP Server能让AI助手访问实时数据、执行操作,为您提供更智能的工作体验和自动化解决方案。

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全面解析Arxiv Search MCPMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器,Arxiv Search MCP能让AI助手访问实时数据、执行操作,为您提供更智能的工作体验和自动化解决方案。

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全面解析Arxiv Search MCP ServerMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器,Arxiv Search MCP Server能让AI助手访问实时数据、执行操作,为您提供更智能的工作体验和自动化解决方案。

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全面解析Arxiv Paper MCPMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器,Arxiv Paper MCP能让AI助手访问实时数据、执行操作,为您提供更智能的工作体验和自动化解决方案。

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命令预览

pip install arxiv-paper-mcp

全面解析Arxivloader MCP Server And ClientMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器,Arxivloader MCP Server And Client能让AI助手访问实时数据、执行操作,为您提供更智能的工作体验和自动化解决方案。

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命令预览

pip install -r requirements.txt

Provides tools to search for arXiv papers, retrieve full-text HTML content via ar5iv, and download papers as PDFs. This server enables LLMs to find and interact with scientific research literature through a standardized interface.

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MCP server for arXiv.org - Search, analyze, and export academic papers with AI assistants. Features advanced paper discovery, citation analysis, trend tracking, and multi-format exports.

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Enables AI assistants to search arXiv's research repository, download papers, and access their content programmatically. Includes specialized prompts for comprehensive academic paper analysis covering methodology, results, and implications.

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Enables querying and discovering the latest arXiv papers by category or keyword, providing structured metadata including titles, authors, summaries, and links for research assistance and literature review workflows.

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Enables searching and retrieving arXiv papers by topic, fetching abstracts by paper ID, and saving markdown content to files. Includes examples of integrating MCP tools with Google Gemini for AI-powered paper research.

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