
Adamamer20 Paper Search Mcp Openai
- 14 repo stars
- Updated September 18, 2025
- adamamer20/paper-search-mcp-openai
ai.smithery/adamamer20-paper-search-mcp-openai is an MCP server that searches and downloads academic papers from major scholarly indexes for agent-driven research.
About
ai.smithery/adamamer20-paper-search-mcp-openai is a Smithery-hosted MCP server that exposes academic search and download workflows to AI coding agents. Developers use it during the idea phase when they need primary sources—market adjacency research, ML baselines, regulatory/medical context, or “has someone already solved this?” checks—without leaving the agent thread. Connect via streamable HTTP at server.smithery.ai with a Smithery API key; the server packages integrations tuned for OpenAI-style agent stacks while remaining usable from Claude Code, Cursor, and Windsurf through standard MCP configuration. It is a connector, not a methodology skill: you trigger searches when prompts need papers, then fold abstracts and PDFs into PRDs, validation notes, or technical spikes. Pair it with your own summarization prompts or skills; it does not replace structured brainstorming or writing-plans, but it shortens the loop from question to citable evidence.
- Multi-source academic search across arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, and Semantic Scholar
- Download papers for offline summarization inside Claude Code, Cursor, or Codex
- Streamable HTTP remote on Smithery with Bearer auth (v1.14.0)
- Backed by adamamer20/paper-search-mcp-openai on GitHub
- MCP tools invoked from the agent—no separate CLI install in-repo
Adamamer20 Paper Search Mcp Openai by the numbers
- Data as of Jul 12, 2026 (Skillselion catalog sync)
claude mcp add --transport http adamamer20-paper-search-mcp-openai https://server.smithery.ai/@adamamer20/paper-search-mcp-openai/mcp --header "Authorization: Bearer YOUR_TOKEN"Add your badge
Show developers this MCP server is listed on Skillselion. Paste this into your README.
| repo stars | ★ 14 |
|---|---|
| Transport | HTTP |
| Auth | Required |
| Last updated | September 18, 2025 |
| Repository | adamamer20/paper-search-mcp-openai ↗ |
What it does
Wire your coding agent to search and download papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, and Semantic Scholar while scoping a product or technical bet.
Who is it for?
Best when you're validating technical or scientific ideas and want citable sources inside Claude Code, Cursor, or Codex without a separate research toolchain.
Skip if: Skip if you need enterprise literature APIs, bulk corpus licensing, or guaranteed full-text access behind paywalls without manual retrieval.
What you get
After you register the Smithery remote, your agent can pull targeted papers and metadata into the same thread you use to scope features and validate assumptions.
- Search results and metadata from configured scholarly sources
- Downloaded paper files usable in the active agent conversation
- Research snippets you can paste into PRDs, specs, or validation docs
By the numbers
- Server version 1.14.0 per server.schema.json
- Six named source families: arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, Semantic Scholar
- Remote transport: streamable-http on Smithery
README.md
Paper Search MCP
A Model Context Protocol (MCP) server for searching and downloading academic papers from multiple sources, including arXiv, PubMed, bioRxiv, and Sci-Hub (optional). Designed for seamless integration with large language models like Claude Desktop.
Table of Contents
Overview
paper-search-mcp is a Python-based MCP server that enables users to search and download academic papers from various platforms. It provides tools for searching papers (e.g., search_arxiv) and downloading PDFs (e.g., download_arxiv), making it ideal for researchers and AI-driven workflows. Built with the MCP Python SDK, it integrates seamlessly with LLM clients like Claude Desktop.
Features
- Multi-Source Support: Search and download papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, IACR ePrint Archive, Semantic Scholar.
- Deep Research Ready: Provides the standardized
searchandfetchtools required by OpenAI Deep Research and ChatGPT connectors. - Standardized Output: Papers are returned in a consistent dictionary format via the
Paperclass. - Asynchronous Tools: Efficiently handles network requests using
httpx. - MCP Integration: Compatible with MCP clients for LLM context enhancement.
- Extensible Design: Easily add new academic platforms by extending the
academic_platformsmodule.
Installation
paper-search-mcp can be installed using uv or pip. Below are two approaches: a quick start for immediate use and a detailed setup for development.
Installing via Smithery
To install paper-search-mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @openags/paper-search-mcp --client claude
Quick Start
For users who want to quickly run the server:
Install Package:
uv add paper-search-mcpConfigure Claude Desktop: Add this configuration to
~/Library/Application Support/Claude/claude_desktop_config.json(Mac) or%APPDATA%\Claude\claude_desktop_config.json(Windows):{ "mcpServers": { "paper_search_server": { "command": "uv", "args": [ "run", "--directory", "/path/to/your/paper-search-mcp", "-m", "paper_search_mcp.server" ], "env": { "SEMANTIC_SCHOLAR_API_KEY": "" // Optional: For enhanced Semantic Scholar features } } } }Note: Replace
/path/to/your/paper-search-mcpwith your actual installation path.
For Development
For developers who want to modify the code or contribute:
Setup Environment:
# Install uv if not installed curl -LsSf https://astral.sh/uv/install.sh | sh # Clone repository git clone https://github.com/openags/paper-search-mcp.git cd paper-search-mcp # Create and activate virtual environment uv venv source .venv/bin/activate # On Windows: .venv\Scripts\activateInstall Dependencies:
# Install project in editable mode uv add -e . # Add development dependencies (optional) uv add pytest flake8
Contributing
We welcome contributions! Here's how to get started:
Fork the Repository: Click "Fork" on GitHub.
Clone and Set Up:
git clone https://github.com/yourusername/paper-search-mcp.git cd paper-search-mcp pip install -e ".[dev]" # Install dev dependencies (if added to pyproject.toml)Make Changes:
- Add new platforms in
academic_platforms/. - Update tests in
tests/.
- Add new platforms in
Submit a Pull Request: Push changes and create a PR on GitHub.
Demo

TODO
Planned Academic Platforms
- [√] arXiv
- [√] PubMed
- [√] bioRxiv
- [√] medRxiv
- [√] Google Scholar
- [√] IACR ePrint Archive
- [√] Semantic Scholar
- PubMed Central (PMC)
- Science Direct
- Springer Link
- IEEE Xplore
- ACM Digital Library
- Web of Science
- Scopus
- JSTOR
- ResearchGate
- CORE
- Microsoft Academic
License
This project is licensed under the MIT License. See the LICENSE file for details.
Happy researching with paper-search-mcp! If you encounter issues, open a GitHub issue.
Recommended MCP Servers
How it compares
Scholarly search MCP integration, not a brainstorming or writing-plans agent skill.
FAQ
Who is ai.smithery/adamamer20-paper-search-mcp-openai for?
Developers and small teams who use AI coding agents and need fast academic search across arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, and Semantic Scholar during product research.
When should I use ai.smithery/adamamer20-paper-search-mcp-openai?
Use it in the idea and validate phases when prompts need papers, citations, or PDFs to support scope, competitive positioning, or technical feasibility.
How do I add ai.smithery/adamamer20-paper-search-mcp-openai to my agent?
Add the Smithery streamable HTTP remote URL for @adamamer20/paper-search-mcp-openai in your MCP client config and set Authorization to Bearer plus your smithery_api_key.