Code of Paper
What it does
Find GitHub implementations of arXiv research papers — paper lookup, ranked code, search.
- Connects 在你的电脑上运行
- Account or key No key needed
- Category 搜索与 AI 记忆
安装
选择你使用的 AI 应用,然后复制设置。
通过 3/3 项检查 · 在你的电脑上运行
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
需要 Code of Paper 的密钥(在开发者网站创建) · 需要先在电脑上安装 Python (uv)(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
打开电脑版 Claude 应用的设置文件
SettingsDeveloperEdit Config
粘贴这些设置并保存文件
{ "mcpServers": { "codeofpaper": { "command": "uvx", "args": [ "codeofpaper" ], "env": { "CODEOFPAPER_API_URL": "your-value" } } } }只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
退出 Claude 再重新打开
试一试
用 Code of Paper 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Code of Paper,或回答中出现 Code of Paper 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 Code of Paper
Code of Paper 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
你可以改用这些方式
A · 使用能连接 Code of Paper 的应用
- 需要 Code of Paper 的密钥(在开发者网站创建) · 需要先在电脑上安装 Python (uv)(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
- 需要 Code of Paper 的密钥(在开发者网站创建) · 需要先在电脑上安装 Python (uv)(只需一次)
- 需要 Code of Paper 的密钥(在开发者网站创建) · 需要先在电脑上安装 Python (uv)(只需一次)
- 需要 Code of Paper 的密钥(在开发者网站创建) · 需要先在电脑上安装 Python (uv)(只需一次)
B · 搜索与 AI 记忆 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
- Context7✓ ChatGPT
- AIHOT✓ ChatGPT
- Sui Knowledge Base (kapa.ai)✓ ChatGPT
可连接 Claude Code,但需要先准备
需要 Code of Paper 的密钥(在开发者网站创建) · 需要先在电脑上安装 Python (uv)(只需一次)
打开终端
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
粘贴这条命令并按 Enter
claude mcp add --scope user codeofpaper --env CODEOFPAPER_API_URL=your-value -- uvx codeofpaper按 Enter 前,把“your-value”改成你的密钥
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
在 Claude Code 中输入 /mcp
应能看到 Code of Paper 在列表中并显示已连接
试一试
用 Code of Paper 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 Code of Paper,或回答中出现 Code of Paper 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor,但需要先准备
需要 Code of Paper 的密钥(在开发者网站创建) · 需要先在电脑上安装 Python (uv)(只需一次)
填写你的密钥
在 Code of Paper 的设置中,CODEOFPAPER_API_URL 还是空的,填入你的密钥并保存
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
在 Cursor 中以 Agent 模式打开 AI 聊天
试一试
用 Code of Paper 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 Code of Paper,或回答中出现 Code of Paper 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code,但需要先准备
需要 Code of Paper 的密钥(在开发者网站创建) · 需要先在电脑上安装 Python (uv)(只需一次)
填写你的密钥
在 Code of Paper 的设置中,CODEOFPAPER_API_URL 还是空的,填入你的密钥并保存
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
在 VS Code 中以 Agent 模式打开 AI 聊天
试一试
用 Code of Paper 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 Code of Paper,或回答中出现 Code of Paper 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
开发者专用:终端命令和 JSON 设置
安装在电脑上
Claude Code
claude mcp add --scope user codeofpaper --env CODEOFPAPER_API_URL=your-value -- uvx codeofpaperClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"codeofpaper": {
"command": "uvx",
"args": [
"codeofpaper"
],
"env": {
"CODEOFPAPER_API_URL": "your-value"
}
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"codeofpaper": {
"command": "uvx",
"args": [
"codeofpaper"
],
"env": {
"CODEOFPAPER_API_URL": "your-value"
}
}
}
}VS Code (mcp.json)
{
"servers": {
"codeofpaper": {
"type": "stdio",
"command": "uvx",
"args": [
"codeofpaper"
],
"env": {
"CODEOFPAPER_API_URL": "your-value"
}
}
}
}需要你填写的值
CODEOFPAPER_API_URLenvOverride the API base URL (default https://api.codeofpaper.com).
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
一览
哪些应用可以使用它
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它能做什么
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
基础检查i
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月12日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 isagelswann 验证,该账户拥有此仓库
- ✓ 通过
仍在维护
代码最后更新于23天前
- ✓ 通过
有许可证
使用 MIT
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行;我们只能读取互联网端点的工具列表
讨论
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
用户评价
还没有评价
与“搜索与 AI 记忆”中的其他服务器比较i
- 星标数多于此分类中其他 6015 个服务器的 76%
- 发布到注册中心的时间比此分类中其他 6015 个服务器的 14% 更新
- 基础检查结果等于或优于此分类中其他 6015 个服务器的 100%
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
常见问题
Code of Paper 安全吗?
它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
它需要哪些密钥或代码?
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在我的电脑上运行还是在云端?
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
它还在维护吗?
GitHub 仓库最后更新于23天前,最新版本(0.3.2)于5个月前进入注册中心。
哪些应用可以使用它?
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
有什么可以替代它?
同一分类中有:Context7, Codebase Memory, Ruflo
同类别的其他选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Codebase Memory
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
作者的 README
打开 README
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Code of Paper CLI
Maintenance mode. This CLI and MCP server are not actively developed. They keep working as long as api.codeofpaper.com is up; issues may go unanswered.
Discover GitHub implementations of research papers — from the terminal.
Search 181k+ arXiv papers and find their code on GitHub. Works for humans and AI agents alike.
Install
pip install codeofpaper
Or with pipx for isolated installs:
pipx install codeofpaper
Requires Python 3.10+. No API key needed — works anonymously at 60 requests/minute.
Quick Start
# Search for papers
codeofpaper search "vision transformers"
Get paper details (arXiv IDs or full URLs both work)
codeofpaper paper 2010.11929 codeofpaper paper https://arxiv.org/abs/2010.11929
Find code implementations
codeofpaper code 1706.03762
Browse trending papers with code
codeofpaper trending --has-code
JSON output for scripts and agents
codeofpaper -o json trending | jq '.trending[] | {title, stars: .max_stars}'
One-shot reproducibility context for an agent: paper + confident repos
(with tier + framework + license) + fork-graph in a single JSON payload.
codeofpaper -o json paper 2010.11929 | jq '{title, repos: [.repos[] | {full_name, tier}], forks: [.fork_graph[] | .full_name]}'
Literature review in one command
codeofpaper research "reinforcement learning" --depth deep
Output Formats
Use -o / --output before the subcommand:
codeofpaper -o json paper 2010.11929
codeofpaper -o quiet search "attention" | head -5 codeofpaper -o csv trending --has-code > papers.csv
| Format | Flag | Use case |
|---|---|---|
| Table | -o table | Human reading (default) |
| JSON | -o json | Scripts, jq pipelines, full response data |
| Quiet | -o quiet | IDs only, one per line — pipe into other commands |
| JSONL | -o jsonl | Streaming, append to files, batch processing |
| BibTeX | -o bibtex | Citation managers, LaTeX bibliographies |
| CSV | -o csv | Spreadsheets, pandas, data analysis |
The shorthand -q is equivalent to -o quiet:
codeofpaper -q search "transformers" | head -3
You can set a default format via config so you don't need -o every time:
codeofpaper auth setup # then edit ~/.config/codeofpaper/config.json
Commands
Discovery
| Command | Description | Example |
|---|---|---|
search | Full-text paper search | codeofpaper search "vision transformers" --has-code |
paper | Paper details by arXiv ID or URL | codeofpaper paper 2010.11929 |
code | GitHub repos implementing a paper | codeofpaper code 1706.03762 |
similar | Semantically similar papers | codeofpaper similar 2010.11929 |
suggest | Autocomplete / quick lookup | codeofpaper suggest "attention" |
random | Random interesting paper | codeofpaper random --quality high |
Browsing
| Command | Description | Example |
|---|---|---|
trending | Trending papers by category | codeofpaper trending --category cs.CV --sort hot |
categories | List categories or get details | codeofpaper categories cs.AI |
conferences | List all conference series | codeofpaper conferences |
conference | Papers from a specific conference | codeofpaper conference neurips_2024 --has-code |
code-drops | Recent conference papers with new code | codeofpaper code-drops --days 7 |
repo | Reverse lookup: repo → paper | codeofpaper repo google-research/vision_transformer |
open | Open paper or repo in browser | codeofpaper open 2010.11929 --code |
Bulk Operations
| Command | Description | Example | |
|---|---|---|---|
research | Structured research overview | codeofpaper research "RL" --depth deep | |
batch | Process multiple IDs from stdin/file | `cat ids.txt \ | codeofpaper batch paper` |
export | Paginated bulk export | codeofpaper export trending -o csv > out.csv |
Configuration
| Command | Description | Example |
|---|---|---|
auth | Manage API key (setup/status/clear) | codeofpaper auth status |
status | Check API health and stats | codeofpaper status |
Command Details
search
codeofpaper search "reinforcement learning" --sort has_code --has-code
codeofpaper search "GAN" --limit 20 --offset 10
Options: --limit, --offset, --sort (relevant, recent, has_code), --has-code, --category.
research
Multi-step orchestrated overview of a research topic:
codeofpaper research "vision transformers" --depth deep
| Depth | Steps | API calls |
|---|---|---|
shallow | Search only + landscape statistics | 1 |
medium | Search + repos for top papers (default) | ~6 |
deep | Search + repos + similar papers from #1 | ~8 |
batch
Process multiple queries or IDs from a file or stdin. Always outputs JSONL regardless of -o:
# From a file
codeofpaper batch paper ids.txt
From stdin
echo -e "2010.11929\n1706.03762" | codeofpaper batch paper
Pipe from another command
codeofpaper -q similar 2010.11929 | codeofpaper batch code
Supported commands: paper, search, code, similar, suggest.
Each line produces one JSON object:
{"input": "2010.11929", "status": "ok", "data": {...}}
{"input": "9999.99999", "status": "error", "error": "Not found"}
Options: --delay (seconds between calls, default 0.5).
export
Paginated bulk export from trending, conference, or search:
codeofpaper export trending --category cs.CV --has-code -o csv > cv.csv
codeofpaper export conference neurips_2024 --has-code -o bibtex > neurips.bib codeofpaper export search "transformers" --max 500 -o jsonl > data.jsonl
Auto-paginates through results (100 per page, 0.5s delay). Options: --max (default 200), --has-code, --category, --days.
Agent Integration
The CLI is designed for AI agent consumption. Key features:
Stable Exit Codes
Agents can branch on exit codes without parsing error messages:
| Exit Code | Meaning | Agent Action |
|---|---|---|
| 0 | Success | Parse stdout |
| 1 | General error | Log and report |
| 2 | Connection error | Retry with backoff |
| 3 | Not found (404) | Skip or try different ID |
| 4 | Rate limited (429) | Wait and retry |
| 5 | Auth required (401/403) | Run codeofpaper auth setup |
Machine-Readable Output
# JSON for structured parsing
codeofpaper -o json paper 2010.11929 | jq '.title'
Quiet mode for ID lists
codeofpaper -q search "attention" | head -5
JSONL for streaming
codeofpaper -o jsonl trending --has-code | while read -r line; do echo "$line" | jq -r '.arxiv_id' done
HTTP Cache
Responses are cached on disk for 30 minutes (~/.cache/codeofpaper/http/), so repeated calls are instant and free.
MCP Server (optional)
Code of Paper ships an optional Model Context Protocol server that exposes paper / code lookup as tools to any MCP-compatible agent — Claude Desktop, Cursor, Continue, Cline, Zed, etc.
Install with the mcp extra:
pip install 'codeofpaper[mcp]'
or, with uv:
uv tool install 'codeofpaper[mcp]'
This adds a codeofpaper-mcp entry point that speaks MCP over stdio.
Wire into Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS), %APPDATA%\Claude\claude_desktop_config.json (Windows), or ~/.config/Claude/claude_desktop_config.json (Linux):
{
"mcpServers": { "codeofpaper": { "command": "uvx", "args": ["--from", "codeofpaper[mcp]", "codeofpaper-mcp"] } } }
This pulls + runs the server on demand — no global install needed. If you've already pip install'd the package, you can replace the command with just "codeofpaper-mcp" and drop args.
Wire into Cursor / Continue / Cline
Most MCP clients accept the same shape:
{
"mcpServers": { "codeofpaper": { "command": "codeofpaper-mcp", "env": { "CODEOFPAPER_API_URL": "https://api.codeofpaper.com" } } } }
Tools exposed
| Tool | Purpose |
|---|---|
paper_lookup(paper_id_or_url) | Paper metadata + confident-tier repos |
code_for_paper(paper_id_or_url, limit, include_possible) | Ranked GitHub repos implementing a paper |
search_papers(query, limit, year, venue, has_code) | Free-text paper search with filters |
All tools are read-only, return plain JSON, and surface API errors as {"error": "...", "status": N} rather than throwing — agents get structured output either way.
Common Workflows
Core Discovery
# Find papers with code about a topic
codeofpaper search "reinforcement learning" --sort has_code --has-code
Get the best repo for a specific paper
codeofpaper code 1706.03762
Accepts arXiv URLs — no need to extract the ID
codeofpaper paper https://arxiv.org/abs/2010.11929
Reverse lookup: what paper does this repo implement?
codeofpaper repo google-research/vision_transformer
Open a paper in the browser, or jump straight to its code
codeofpaper open 2010.11929 codeofpaper open 2010.11929 --code
Browsing & Monitoring
# What's trending in computer vision?
codeofpaper trending --category cs.CV --sort hot
Conference papers that just got new code
codeofpaper code-drops --days 7
NeurIPS 2024 oral papers with code
codeofpaper conference neurips_2024 --track oral --has-code
Daily monitoring: what's new in my field?
codeofpaper trending --category cs.CV --days 1 -o json >> ~/research/daily_cv.jsonl
Composable Pipelines
# Find implementations of a paper's related work
codeofpaper similar 2010.11929 -o quiet | codeofpaper batch code
Batch process a reading list
cat reading_list.txt | codeofpaper batch paper > enriched.jsonl
Cross-reference with GitHub CLI
codeofpaper code 1706.03762 -o quiet | head -1 | xargs gh repo view
Export conference papers as BibTeX
codeofpaper export conference neurips_2024 --has-code -o bibtex > neurips2024_code.bib
Bulk export a category for meta-analysis
codeofpaper export trending --category cs.CV --has-code --days 365 -o csv > cv_with_code.csv
Multi-Step Scripts
# Find a paper → get top repo → clone it
REPO=$(codeofpaper search "attention is all you need" -o quiet | head -1 | \ xargs codeofpaper code -o json | jq -r '.top_repos[0].full_name') gh repo clone "$REPO"
Discover a random paper and explore its neighborhood
ID=$(codeofpaper random --quality high -o quiet) codeofpaper paper "$ID" codeofpaper similar "$ID" codeofpaper code "$ID"
Quick paper lookup in a script
ARXIV_ID="2010.11929" TITLE=$(codeofpaper -o json paper "$ARXIV_ID" | jq -r '.title') echo "Paper: $TITLE"
Configuration
Config is stored as JSON via platformdirs:
| OS | Path |
|---|---|
| Linux | ~/.config/codeofpaper/config.json |
| macOS | ~/Library/Application Support/codeofpaper/config.json |
| Windows | %APPDATA%\codeofpaper\config.json |
Fields:
{
"api_url": "https://api.codeofpaper.com", "api_key": null, "default_format": "table", "ca_bundle": null }
No config file needed — everything works out of the box with sensible defaults.
Priority Chain
Options are resolved in this order (first wins):
- CLI flag (
--api-url,--api-key,--ca-bundle,-o) - Environment variable (
CODEOFPAPER_API_URL,CODEOFPAPER_API_KEY, `CODEOFP