学习研究来源：GitHub 协议：MIT 协议已标注

paper-search-mcp

通过论文搜索服务定位学术资料，并把结果接入 Agent 研究流程。

2.6K GitHub stars 2026-09-05 星标同步 2026-07-16 收录时间

#paper#search#mcp

快速判断

01这个 Skill 是干嘛的: 通过论文搜索服务发现学术资料，并把检索结果接入 Agent 研究。
02它能解决什么问题: 解决跨学术来源检索步骤分散、结果格式不统一和文献难进入后续分析的问题。
03它适合谁来用: 适合需要程序化查找论文、构建文献池的研究者和研究型 Agent。

paper-search-mcp

通过论文搜索服务定位学术资料，并把结果接入 Agent 研究流程。

主要能力

Search, download, and read academic papers from 20+ sources (arXiv, PubMed, Semantic Scholar, CrossRef, etc). Use when the user asks to find papers, search for research, look up academic literature, download a paper PDF, or extract text from a paper.

使用方式

仓库级安装会保留完整目录；本次核验的入口是 claude-code/SKILL.md。使用前先阅读英文 README 与原始 SKILL.md，并按当前 Agent 的目录规范安装。

适用边界

检索覆盖面受数据源限制，系统综述仍需多数据库交叉检索。

许可与来源

来源：GitHub 公开仓库。核验许可：MIT。本页是贴近原仓库结构的中文导读，具体参数、依赖和更新记录以英文 README 为准。

Paper Search MCP

A Model Context Protocol (MCP) server for searching and downloading academic papers from multiple sources. The project follows a free-first strategy: prioritize open and public data sources, support optional API keys when they improve stability or coverage, and keep source-specific connectors extensible for advanced users.

---

Overview
Project Principles
Features
Source Strategy
Sci-Hub Notice
Installation

- Claude Code (Skill) - Method 1 — Smithery - Method 2 — uvx - Method 3 — uv - Method 4 — pip - Method 5 — npx - Method 6 — Docker - Method 7 — Clone & run from source - Environment Variables

Contributing
Demo
Star History
License
TODO

---

Overview

paper-search-mcp is a Python-based tool for searching and downloading academic papers from various platforms. It provides tools for searching papers, downloading PDFs, and extracting text, making it ideal for researchers and AI-driven workflows. It can be used as an MCP server (for Claude Desktop and other MCP clients) or as a Claude Code skill with a CLI interface.

Project Principles

Free-First: Public and open sources are the default roadmap. Paid or restricted sources are not the core direction of this project.
Optional API Keys: API keys are supported only when they improve stability, rate limits, or metadata quality. The MCP should still be usable without them whenever possible.
LLM-Friendly Retrieval: Search results should be standardized, deduplicated, and as complete as possible for downstream LLM workflows.
Source Transparency: Different sources have different strengths. The MCP should make those tradeoffs explicit instead of pretending every source supports full-text retrieval.

---

Features

Two-Layer Architecture:

- Layer 1 (Unified Tooling): High-level search_papers for multi-source concurrent search & deduplication, and download_with_fallback relying on publisher open access links with sequential fallbacks. - Layer 2 (Platform Connectors): Modular connectors for specific academic platforms (arXiv, PubMed, bioRxiv, Semantic Scholar, etc.) equipped with intelligent DOI extraction via regex text analysis or API fields.

Multi-Source Support: Search and download papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, IACR ePrint Archive, Semantic Scholar, Crossref, OpenAlex, PubMed Central (PMC), CORE, Europe PMC, dblp, OpenAIRE, CiteSeerX, DOAJ, BASE, Zenodo, HAL, SSRN, Unpaywall (DOI lookup), and optional Sci-Hub workflows.
Standardized Output: Papers are returned in a consistent dictionary format via the Paper class.
Free-First Design: Open and public sources are prioritized before any optional commercial or restricted integrations.
Optional API-Key Enhancement: Sources like Semantic Scholar can work better with a user-provided API key, but are not intended to force paid usage.
Discovery + Retrieval Workflow: Google Scholar and Crossref can be used for discovery and DOI backfilling, while open repositories and publisher links are used for lawful full-text resolution where available.
OA-First Fallback Chain: download_with_fallback now follows source-native download → OpenAIRE/CORE/Europe PMC/PMC discovery → Unpaywall DOI resolution → optional Sci-Hub.
MCP Integration: Compatible with MCP clients for LLM context enhancement.
Extensible Design: Easily add new academic platforms by extending the academic_platforms module.

Source Strategy

The long-term goal is not to depend on a single search engine, but to combine multiple free and public sources with clear roles:

Open metadata backbone: Crossref, OpenAlex, Semantic Scholar, dblp, CiteSeerX, SSRN, Unpaywall (DOI-centric OA metadata).
Discipline-specific sources: arXiv, PubMed, PubMed Central, Europe PMC, IACR.
Open-access full-text sources: arXiv, PMC, CORE, OpenAIRE, DOAJ, BASE, Zenodo, HAL, publisher open-access links.
Discovery and DOI recovery: Google Scholar can be useful for finding titles, versions, and DOI clues when other public metadata sources are incomplete.

Recommended free-first roadmap:

Keep current public sources stable.
Add OpenAlex as a broad free metadata source.
Add PubMed Central and Europe PMC for stronger biomedical full-text access.
Add CORE and OpenAIRE for repository-based open-access retrieval.
Use Google Scholar mainly as a discovery fallback, not as the primary canonical source.

Platform Capability Matrix

This matrix reflects verified live-integration results from functional and end-to-end regression tests in this repository. Columns show the highest capability level observed under normal conditions.

Platform	Search	Download	Read	Notes
arXiv	✅	✅	✅	Open API; reliable
PubMed	✅	❌	⚠️ info-only	Open API; reliable
bioRxiv	✅	✅	✅	Open API; reliable
medRxiv	✅	✅	✅	Open API; reliable
Google Scholar	⚠️	❌	❌	Bot-detection active; set `PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL`
IACR	✅	✅	✅	Open API; reliable
Semantic Scholar	✅	✅ (OA)	✅ (OA)	Works without key (rate-limited); key improves limits; key rejection (403) retried automatically without key
Crossref	✅	❌	⚠️ info-only	Open API; reliable
OpenAlex	✅	❌	⚠️ info-only	Open API; reliable
PMC	✅	✅ (OA only)	✅ (OA only)	OA PDFs only; direct download may be blocked by some proxy environments
CORE	✅	✅ (record-dependent)	✅ (record-dependent)	Free key recommended; connector retries with backoff and falls back to key-less on 401/403
Europe PMC	✅	✅ (OA)	✅ (OA)	OA PDFs only; direct download may be blocked by some proxy environments
dblp	✅	❌	⚠️ info-only	Open API; reliable
OpenAIRE	✅	❌	❌	Open API; retries 3× with escalating request profiles on transient 403
CiteSeerX	⚠️	✅ (record-dependent)	⚠️	API endpoint intermittently unavailable / redirects to web archive
DOAJ	✅	⚠️ (URL-dependent)	⚠️ (URL-dependent)	PDF availability varies by article; free key raises rate limits
BASE	⚠️	✅ (record-dependent)	✅ (record-dependent)	OAI-PMH endpoint requires institutional IP registration; returns empty gracefully otherwise
Zenodo	✅	✅ (record-dependent)	✅ (record-dependent)	Open API; reliable
HAL	✅	✅ (record-dependent)	✅ (record-dependent)	Open API; reliable
SSRN	⚠️	⚠️ best-effort	⚠️ best-effort	403 bot-detection active; public PDF only
Unpaywall	✅ (DOI lookup)	❌	❌	Requires `PAPER_SEARCH_MCP_UNPAYWALL_EMAIL`
Sci-Hub (optional)	⚠️ fallback-only	✅	❌	Optional; unstable mirrors; user responsibility
IEEE Xplore 🔑	🚧 skeleton	🚧 skeleton	🚧 skeleton	Requires `PAPER_SEARCH_MCP_IEEE_API_KEY` to activate
ACM DL 🔑	🚧 skeleton	🚧 skeleton	🚧 skeleton	Requires `PAPER_SEARCH_MCP_ACM_API_KEY` to activate

✅ = reliable in live tests. ⚠️ = works but subject to upstream instability or access restrictions. ❌ = not supported. 🔑 = key required. 🚧 = skeleton only.

---

Credential & API Key Requirements

All keys are optional unless noted. Configure them in ~/.config/paper-search-mcp/.env (preferred) or as shell exports.

Environment Variable	Provider	Required?	How to obtain
`PAPER_SEARCH_MCP_UNPAYWALL_EMAIL`	Unpaywall	Yes (Unpaywall disabled without it)	Any valid email; register at unpaywall.org
`PAPER_SEARCH_MCP_CORE_API_KEY`	CORE	Recommended	Free at core.ac.uk/services/api
`PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY`	Semantic Scholar	Optional	Free at semanticscholar.org — improves rate limits
`PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL`	Google Scholar	Optional	Your HTTP/HTTPS proxy URL — bypasses bot-detection
`PAPER_SEARCH_MCP_DOAJ_API_KEY`	DOAJ	Optional	Free at doaj.org — raises hourly rate limit
`PAPER_SEARCH_MCP_ZENODO_ACCESS_TOKEN`	Zenodo	Optional	Free at zenodo.org — required for private records
`PAPER_SEARCH_MCP_IEEE_API_KEY`	IEEE Xplore	Required to activate	Free at developer.ieee.org
`PAPER_SEARCH_MCP_ACM_API_KEY`	ACM DL	Required to activate	See libraries.acm.org/digital-library/acm-open

All variables follow the PAPER_SEARCH_MCP_<NAME> prefix scheme. Legacy names without the prefix (e.g. CORE_API_KEY, UNPAYWALL_EMAIL) are still supported for backward compatibility.

---

Known Upstream Limitations

Some search failures are caused by external provider instability, not by bugs in this project:

Source	Symptom	Cause	Workaround
Google Scholar	Returns 0 results / empty HTML	Bot-detection (CAPTCHA)	Set `PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL` to a proxy
Semantic Scholar	429 rate-limited responses	Anonymous access rate limit	Set `PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY`; if key is rejected (403) connector automatically retries without key
CORE	500 / timeout errors	Unauthenticated rate limiting	Set `PAPER_SEARCH_MCP_CORE_API_KEY` (free); connector retries with exponential backoff and falls back to key-less on 401/403
OpenAIRE	Transient 403 responses	IP-based session rate limiting	Connector retries 3× per profile, escalating: plain session → XML Accept header → raw `requests.get` with Mozilla UA
CiteSeerX	404 via web archive redirect	PSU endpoint intermittently redirects to archive	No workaround; connector returns empty gracefully
BASE	Search returns 0 results	OAI-PMH endpoint requires institutional IP registration	Register at base-search.net for API access; connector returns empty gracefully otherwise
SSRN	HTTP 403	Bot-detection (Cloudflare)	No workaround; connector tries two endpoints and returns a clear message on failure
PMC / Europe PMC	PDF download ProxyError	Local proxy blocking direct HTTPS PDF download	Disable proxy or use `download_with_fallback` instead
Unpaywall	Skipped entirely	`UNPAYWALL_EMAIL` env var not set	Set `PAPER_SEARCH_MCP_UNPAYWALL_EMAIL` in `~/.config/paper-search-mcp/.env`

Optional Paid Platform Connectors (Phase 3)

IEEE Xplore and ACM Digital Library connectors are included as opt-in skeletons. They are disabled by default — no API calls are made unless you explicitly configure the corresponding keys.

Platform	Env Var	Status
IEEE Xplore	`PAPER_SEARCH_MCP_IEEE_API_KEY`	🚧 skeleton — search registered, download/read raise `NotImplementedError`
ACM Digital Library	`PAPER_SEARCH_MCP_ACM_API_KEY`	🚧 skeleton — search registered, download/read raise `NotImplementedError`

How to enable:

export PAPER_SEARCH_MCP_IEEE_API_KEY=<your_ieee_key>       # free key at https://developer.ieee.org/
export PAPER_SEARCH_MCP_ACM_API_KEY=<your_acm_key>         # see https://libraries.acm.org/digital-library

Once a key is set, the corresponding source is automatically added to ALL_SOURCES and its MCP tools (search_ieee / search_acm, download_ieee / download_acm, read_ieee_paper / read_acm_paper) are registered at server startup.

Without a key the connectors log a startup warning only — the rest of the server is unaffected.

Free Source Expansion (Phase 4)

Three additional free-source connectors are now integrated into the MCP server:

zenodo: Official Zenodo REST API connector (search + record-dependent PDF/read support).
hal: HAL public API connector (search + record-dependent PDF/read support).
ssrn: Discovery-first connector with hardened parser and best-effort download/read when a direct public PDF link is available.
unpaywall: DOI-centric OA metadata source for standalone lookup (search_unpaywall) and fallback URL resolution.

SSRN integration remains compliance-first: it only attempts direct public PDF links exposed by SSRN pages. If login/restricted delivery is required, the connector returns a clear message instead of bypassing access controls.

Sci-Hub Notice

Sci-Hub support can remain available as an optional connector for users who explicitly choose to enable it, but it should not be treated as the default or recommended full-text path.

Availability is unstable and mirrors change frequently.
Legal and policy risks vary by jurisdiction.
README and tool descriptions should clearly state that users are responsible for enabling and using it.
Open-access and publisher-permitted sources should be tried first whenever possible.

---

Installation

Choose the method that best fits your workflow. All methods support the same optional API keys.

---

Claude Code (Skill) — recommended for Claude Code users

Install as a Claude Code skill instead of an MCP server. This gives Claude automatic access to paper search when you mention finding papers, academic literature, etc. — no MCP configuration needed.

Prerequisites: uv and Claude Code.

Step 1 — Install the CLI:

uv tool install paper-search-mcp

Step 2 — Install the skill:

mkdir -p ~/.claude/skills/paper-search
curl -fsSL https://raw.githubusercontent.com/openags/paper-search-mcp/main/claude-code/SKILL.md \
  -o ~/.claude/skills/paper-search/SKILL.md

Step 3 (optional) — Configure API keys:

Create ~/.config/paper-search-mcp/.env for optional API keys (see Environment Variables).

That's it. Next time you start Claude Code, just ask it to find papers — the skill activates automatically. For example:

"Find me recent papers on CRISPR base editing"
"Search arxiv and semantic scholar for transformer attention mechanisms"
"Download the PDF for arxiv paper 2106.12345"

The skill uses a CLI (paper-search) that wraps the same library as the MCP server, outputting JSON for search/download and plain text for read.

---

MCP Server Config file locations (for methods below) - macOS: ~/Library/Application Support/Claude/claude_desktop_config.json - Windows: %APPDATA%\Claude\claude_desktop_config.json - Linux: ~/.config/Claude/claude_desktop_config.json

---

Method 1 — Smithery (one-command, recommended for Claude Desktop)

npx -y @smithery/cli install @openags/paper-search-mcp --client claude

Smithery automatically writes the correct config block for you. No manual JSON editing needed.

---

Method 2 — `uvx` (no install, always latest)

uvx runs the package directly from PyPI without a permanent install. Requires uv.

# Install uv (skip if already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh

⚠️ macOS note: uvx generated wrapper scripts rely on realpath, which is not included in macOS by default. If you see a realpath: command not found error, either install GNU coreutils (brew install coreutils) or use Method 3 (uv run) instead — it does not have this limitation.

Claude Desktop config:

{
  "mcpServers": {
    "paper-search-mcp": {
      "command": "uvx",
      "args": ["paper-search-mcp"],
      "env": {
        "PAPER_SEARCH_MCP_UNPAYWALL_EMAIL": "your@email.com",
        "PAPER_SEARCH_MCP_CORE_API_KEY": "",
        "PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY": "",
        "PAPER_SEARCH_MCP_ZENODO_ACCESS_TOKEN": "",
        "PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL": "",
        "PAPER_SEARCH_MCP_IEEE_API_KEY": "",
        "PAPER_SEARCH_MCP_ACM_API_KEY": ""
      }
    }
  }
}

---

Method 3 — `uv` (persistent install)

uv tool install paper-search-mcp

Claude Desktop config:

{
  "mcpServers": {
    "paper-search-mcp": {
      "command": "uv",
      "args": ["tool", "run", "paper-search-mcp"],
      "env": {
        "PAPER_SEARCH_MCP_UNPAYWALL_EMAIL": "your@email.com",
        "PAPER_SEARCH_MCP_CORE_API_KEY": "",
        "PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY": "",
        "PAPER_SEARCH_MCP_ZENODO_ACCESS_TOKEN": "",
        "PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL": "",
        "PAPER_SEARCH_MCP_IEEE_API_KEY": "",
        "PAPER_SEARCH_MCP_ACM_API_KEY": ""
      }
    }
  }
}

---

Method 4 — `pip` (standard Python install)

pip install paper-search-mcp

Claude Desktop config:

{
  "mcpServers": {
    "paper-search-mcp": {
      "command": "python",
      "args": ["-m", "paper_search_mcp.server"],
      "env": {
        "PAPER_SEARCH_MCP_UNPAYWALL_EMAIL": "your@email.com",
        "PAPER_SEARCH_MCP_CORE_API_KEY": "",
        "PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY": "",
        "PAPER_SEARCH_MCP_ZENODO_ACCESS_TOKEN": "",
        "PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL": "",
        "PAPER_SEARCH_MCP_IEEE_API_KEY": "",
        "PAPER_SEARCH_MCP_ACM_API_KEY": ""
      }
    }
  }
}

If python is not on your PATH, replace it with the full path (e.g. /usr/bin/python3 or C:\Python311\python.exe). Run which python3 / where python to find it.

---

Method 5 — `npx` (via Smithery CLI, no local Python needed)

npx -y @smithery/cli run @openags/paper-search-mcp

Claude Desktop config:

{
  "mcpServers": {
    "paper-search-mcp": {
      "command": "npx",
      "args": ["-y", "@smithery/cli", "run", "@openags/paper-search-mcp"],
      "env": {
        "PAPER_SEARCH_MCP_UNPAYWALL_EMAIL": "your@email.com",
        "PAPER_SEARCH_MCP_CORE_API_KEY": "",
        "PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY": ""
      }
    }
  }
}

---

Method 6 — Docker

docker build -t paper-search-mcp .
docker run --rm -i \
  -e PAPER_SEARCH_MCP_UNPAYWALL_EMAIL=your@email.com \
  -e PAPER_SEARCH_MCP_CORE_API_KEY=your_core_key \
  paper-search-mcp

Claude Desktop config:

{
  "mcpServers": {
    "paper-search-mcp": {
      "command": "docker",
      "args": ["run", "--rm", "-i", "paper-search-mcp"],
      "env": {
        "PAPER_SEARCH_MCP_UNPAYWALL_EMAIL": "your@email.com",
        "PAPER_SEARCH_MCP_CORE_API_KEY": "",
        "PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY": "",
        "PAPER_SEARCH_MCP_ZENODO_ACCESS_TOKEN": "",
        "PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL": "",
        "PAPER_SEARCH_MCP_IEEE_API_KEY": "",
        "PAPER_SEARCH_MCP_ACM_API_KEY": ""
      }
    }
  }
}

---

Method 7 — Clone & run from source (development / recommended for macOS local)

This is the most reliable method on macOS — no wrapper scripts, no realpath issues.

# 1. Install uv (skip if already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh

# 2. Clone repo
git clone https://github.com/openags/paper-search-mcp.git
cd paper-search-mcp

# 3. Verify it runs (uv auto-resolves dependencies, no manual install needed)
uv run -m paper_search_mcp.server

Claude Desktop config (replace the directory path with your actual clone location):

{
  "mcpServers": {
    "paper-search-mcp": {
      "command": "uv",
      "args": [
        "run",
        "--directory", "/path/to/paper-search-mcp",
        "-m", "paper_search_mcp.server"
      ],
      "env": {
        "PAPER_SEARCH_MCP_UNPAYWALL_EMAIL": "your@email.com",
        "PAPER_SEARCH_MCP_CORE_API_KEY": "",
        "PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY": "",
        "PAPER_SEARCH_MCP_ZENODO_ACCESS_TOKEN": "",
        "PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL": "",
        "PAPER_SEARCH_MCP_IEEE_API_KEY": "",
        "PAPER_SEARCH_MCP_ACM_API_KEY": ""
      }
    }
  }
}

For example, if you cloned to /Users/mac/Pengsong/paper-search-mcp:

"args": ["run", "--directory", "/Users/mac/Pengsong/paper-search-mcp", "-m", "paper_search_mcp.server"]

uv run automatically installs dependencies into an isolated environment on first run — no pip install or venv needed.

For active development, optionally install an editable copy:

uv venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
uv pip install -e ".[dev]"

---

Environment Variables (`.env` file)

Instead of putting keys directly in the JSON config you can store them in the user config file (auto-loaded on startup):

mkdir -p ~/.config/paper-search-mcp
curl -fsSL https://raw.githubusercontent.com/openags/paper-search-mcp/main/.env.example \
  -o ~/.config/paper-search-mcp/.env
$EDITOR ~/.config/paper-search-mcp/.env

PAPER_SEARCH_MCP_UNPAYWALL_EMAIL=your@email.com
PAPER_SEARCH_MCP_CORE_API_KEY=
PAPER_SEARCH_MCP_SEMANTIC_SCHOLAR_API_KEY=
PAPER_SEARCH_MCP_ZENODO_ACCESS_TOKEN=
PAPER_SEARCH_MCP_GOOGLE_SCHOLAR_PROXY_URL=
PAPER_SEARCH_MCP_IEEE_API_KEY=
PAPER_SEARCH_MCP_ACM_API_KEY=

To use a custom path: export PAPER_SEARCH_MCP_ENV_FILE=/absolute/path/to/.env

Legacy variable names without the PAPER_SEARCH_MCP_ prefix (e.g. CORE_API_KEY, UNPAYWALL_EMAIL) are still supported for backward compatibility.

---

Contributing

We welcome contributions! Here's how to get started:

Fork the Repository:

Click "Fork" on GitHub.

Clone and Set Up:

``bash git clone https://github.com/yourusername/paper-search-mcp.git cd paper-search-mcp uv venv && source .venv/bin/activate uv pip install -e ".[dev]" ``

Make Changes:

- Add new platforms in academic_platforms/. - Update tests in tests/.

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
[√] Crossref
[√] PubMed Central (PMC)
[√] CORE
[√] Europe PMC
[√] Sci-Hub warning and enablement docs

Development Tasks

[√] Fix Async search bugs and ensure reliable fast MCP events
[√] End-to-End full pipeline testing script (search, parse, download)
[√] Establish two-layer federated architecture (Layer 1 tool: search_papers)
[√] Ensure pervasive DOI extraction across metadata fields & abstract fallbacks
[ ] Citation graph & Paper relation context feature
[√] Expand full-stack OpenAlex provider

Priority Free and Open Sources

[√] PubMed Central (PMC)
[√] CORE
[√] OpenAlex
[√] Europe PMC
[√] OpenAIRE
[√] dblp
[√] CiteSeerX
[√] DOAJ
[√] BASE
[√] Zenodo
[√] HAL
[√] SSRN (discovery + best-effort full-text)
[√] Unpaywall (standalone DOI search source)

Optional and Non-Core Integrations

[ ] ResearchGate
[ ] JSTOR
[ ] ScienceDirect
[ ] Springer Link
[√] IEEE Xplore (optional skeleton — activate with IEEE_API_KEY)
[√] ACM Digital Library (optional skeleton — activate with ACM_API_KEY)
[ ] Web of Science
[ ] Scopus

---

Star History

---

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.

安装

选择适合你当前 Agent 的方式

01 · 发给当前 Agent自动识别兼容方式与安装位置

请帮我安装「paper-search-mcp」。它是一个 Agent Skill 或仓库级 Skill 包。
来源：https://github.com/openags/paper-search-mcp

请先阅读仓库的 README、SKILL.md 与安装说明，再按我当前使用的 Agent 的原生规范安装；如果仓库兼容 Agent Skills CLI，优先执行「npx skills add https://github.com/openags/paper-search-mcp」。不要写死为某一个 Agent 的专用目录，不覆盖已有同名文件。完成后告诉我实际安装位置、启用方式和验证结果。

在 GitHub 查看原文

本站按仓库级 package 收录，安装时克隆完整 paper-search-mcp 仓库；已核验的 skill 入口为 claude-code/SKILL.md。

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paper-search-mcp

主要能力

使用方式

适用边界

许可与来源

Paper Search MCP

Table of Contents

Overview

Project Principles

Features

Source Strategy

Platform Capability Matrix

Credential & API Key Requirements

Known Upstream Limitations

Optional Paid Platform Connectors (Phase 3)

Free Source Expansion (Phase 4)

Sci-Hub Notice

Installation

Claude Code (Skill) — recommended for Claude Code users

Method 1 — Smithery (one-command, recommended for Claude Desktop)

Method 2 — uvx (no install, always latest)

Method 3 — uv (persistent install)

Method 4 — pip (standard Python install)

Method 5 — npx (via Smithery CLI, no local Python needed)

Method 6 — Docker

Method 7 — Clone & run from source (development / recommended for macOS local)

Environment Variables (.env file)

Contributing

Demo

TODO

Planned Academic Platforms

Development Tasks

Priority Free and Open Sources

Optional and Non-Core Integrations

Star History

License

Method 2 — `uvx` (no install, always latest)

Method 3 — `uv` (persistent install)

Method 4 — `pip` (standard Python install)

Method 5 — `npx` (via Smithery CLI, no local Python needed)

Environment Variables (`.env` file)