Search Papers — quickly find, filter, and analyze arXiv academic papers with powerful search and citation tools.
by saidiibrahim·Updated Apr 13, 2026Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
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Ollama
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Local RAG
Local RAG enables semantic document search using retrieval augmented generation (RAG) without external API calls.
Sequential Thinking Multi-Agent System
Orchestrate complex problem-solving with our multi agent system—specialized agents offer deep, structured, and parallel
Search Papers has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Search Papers surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Search Papers is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, Search Papers benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Strong directory entry: Search Papers surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated Search Papers against two servers with overlapping tools; this profile had the clearer scope statement.
Search Papers is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Search Papers reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Useful MCP listing: Search Papers is the kind of server we cite when onboarding engineers to host + tool permissions.
We wired Search Papers into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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Claude Desktop configuration
{
"mcpServers": {
"search-papers": {
"url": "https://search-papers.com/sse",
"env": null
}
}
}Search and analyze academic papers from arXiv with advanced filtering and citation tracking capabilities.
Search Papers is a community-built MCP server published by saidiibrahim that provides AI assistants with tools and capabilities via the Model Context Protocol. Search Papers — quickly find, filter, and analyze arXiv academic papers with powerful search and citation tools. It is categorized under ai ml. This server exposes 10 tools that AI clients can invoke during conversations and coding sessions.
You can install Search Papers in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
Empower your agents to search, analyse, and explore academic papers from arXiv autonomouly.
{
"search-papers": {
"command": "npx",
"args": ["mcp-remote", "https://search-papers.com/sse"]
}
}
claude mcp add --transport sse cloudflare-docs -s project https://search-papers.com/sse
{
"search-papers": {
"type": "sse",
"url": "https://search-papers.com/sse"
}
}
[mcp_servers.search-papers]
command = "npx"
args = ["https://search-papers.com/sse"]
Search & Discovery Tools:
advanced_search - Multi-field search with date ranges and sortingsearch_by_author - Find all papers by specific authorssearch_by_category - Browse papers in ArXiv categoriessearch_by_date_range - Find papers within time periodsPaper Analysis Tools:
get_paper_by_id - Retrieve complete paper informationget_paper_versions - Track all versions of a paperget_citations - Extract ArXiv citations from papersget_related_papers - Discover similar papersExport & Bibliography:
export_bibliography - Export in BibTeX or JSON formatAI-Powered Prompts:
literature_review - Generate comprehensive literature reviewsresearch_gaps - Identify research gaps and opportunitiespaper_comparison - Compare multiple paperstrend_analysis - Analyze research trends over timeResources:
categories://list - Browse all ArXiv categoriestrending://{category}/{days} - Get trending papers"Find papers on transformer architectures by Vaswani published after 2023"
"Search for quantum computing papers in the last month"
"Show me all papers by Geoffrey Hinton with their affiliations"
"Get all versions of paper 2401.12345 and show how it evolved"
"Extract citations from paper 2401.12345"
"Find papers related to arXiv:2301.00001"
"Generate a literature review on vision transformers focusing on architecture innovations"
"Identify research gaps in federated learning over the last 2 years"
"Compare papers 2401.12345, 2401.67890, and 2401.11111 on methodology"
"Analyze trends in large language models research over 5 years"
"Export these 5 papers in BibTeX format for my thesis"
"Show trending AI papers from the last week"
"List all computer science categories in ArXiv"
Contributions are welcome! Please feel free to submit a Pull Request.
This repository is licensed under the Apache-2.0 License
Built with ❤️ by Ibrahim Saidi and AI agents.
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.