AI Research Assistant MCP
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- AlicenseAqualityDmaintenanceEnables searching, downloading, and managing academic papers from arXiv.org through natural language interactions. Provides tools for paper discovery, PDF downloads, and local paper collection management.41MIT
- FlicenseNot gradedqualityBmaintenanceEnables LLMs to search arXiv, extract and analyze paper content, and build a personal semantically-searchable research library with saved papers and notes.-
- AlicenseNot gradedqualityCmaintenanceEnables AI-powered academic paper discovery, search, and analysis from arXiv with advanced features like semantic search, citation network analysis, and multi-format exports (BibTeX, RIS, JSON, CSV). Provides intelligent research assistance through specialized AI prompts for summarization, trend tracking, and literature review automation.17MIT
- FlicenseNot gradedqualityCmaintenanceEnables searching, ingesting, and querying academic papers using natural language, with integration to arXiv and Semantic Scholar.-
- FlicenseNot gradedqualityDmaintenanceEnables intelligent academic paper discovery through ArXiv search and AI-powered semantic similarity analysis. Helps researchers find and rank the most relevant papers using natural language queries and state-of-the-art sentence transformers.-
- AlicenseNot gradedqualityDmaintenanceManages arXiv papers: search, download, analyze, and save AI-generated summaries. Enables AI assistants to interact with the arXiv platform.MIT
TDQS
Scored across 10 tools
Each tool addresses a distinct research task: searching external papers, retrieving details, summarizing, comparing, extracting methodology, managing a personal library, identifying limitations, finding gaps, and saving papers. No two tools overlap in intent; even summarize_paper and extract_methodology focus on different aspects (overall summary vs. specific technical approach).
All tool names follow a consistent verb_noun pattern using snake_case (e.g., search_papers, get_paper, list_saved_papers, find_research_gaps). The verbs clearly describe the action and the nouns the target, making the naming predictable and easy to parse.
With 10 tools, the server is well-scoped for a research assistant. Each tool serves a necessary function in the search-analyze-save pipeline, and the count is neither sparse nor bloated, matching the domain scope appropriately.
The tool surface covers the core research workflow: search, retrieve, summarize, compare, extract methodology, identify limitations, find gaps, and manage a saved library. The only minor omission is a removal/delete operation for saved papers, but this does not create a dead end for typical use cases.