litra-paper-search-mcp

litra-paper-search-mcp

AI-powered academic paper search MCP server with relevance scoring, summarization, author search, and credit checking. Enables users to search papers naturally and get scored results.

Category
访问服务器

README

litra-paper-search-mcp

npm version License: MIT

MCP server for Litra.ai – AI-powered academic paper search with relevance scoring and summarization.

Features

  • search_papers – Search academic papers with AI-powered relevance scoring (1-10) and summarization. Year filtering is available but currently experimental (see Known limitations).
  • search_author – Search papers by author name. Returns author profile (affiliation, h-index) and publications.
  • check_credits – Check your Litra.ai credit balance and subscription plan.

Prerequisites

  • Node.js 18 or higher
  • A Litra.ai account with a paid plan (Mini or above)

Get Your API Key

  1. Sign in at litra-ai.com/account
  2. Navigate to the API Keys section
  3. Click Create API Key and copy the key (it is shown only once)

Setup

Claude Code

claude mcp add litra-paper-search -- npx -y litra-paper-search-mcp

Then set the environment variable LITRA_API_KEY in your shell or Claude Code config.

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "litra-paper-search": {
      "command": "npx",
      "args": ["-y", "litra-paper-search-mcp"],
      "env": {
        "LITRA_API_KEY": "litra_xxxxxxxxxxxx"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "litra-paper-search": {
      "command": "npx",
      "args": ["-y", "litra-paper-search-mcp"],
      "env": {
        "LITRA_API_KEY": "litra_xxxxxxxxxxxx"
      }
    }
  }
}

Windsurf

Add to .windsurf/mcp.json:

{
  "mcpServers": {
    "litra-paper-search": {
      "command": "npx",
      "args": ["-y", "litra-paper-search-mcp"],
      "env": {
        "LITRA_API_KEY": "litra_xxxxxxxxxxxx"
      }
    }
  }
}

Cline

Add to .cline/mcp_settings.json:

{
  "mcpServers": {
    "litra-paper-search": {
      "command": "npx",
      "args": ["-y", "litra-paper-search-mcp"],
      "env": {
        "LITRA_API_KEY": "litra_xxxxxxxxxxxx"
      }
    }
  }
}

GitHub Copilot (VS Code)

Add to .vscode/mcp.json:

{
  "servers": {
    "litra-paper-search": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "litra-paper-search-mcp"],
      "env": {
        "LITRA_API_KEY": "litra_xxxxxxxxxxxx"
      }
    }
  }
}

Tools

search_papers

Search academic papers with AI-powered relevance scoring and summarization.

Parameter Type Required Description
query string Yes Natural language search query (1-500 chars)
max_results number No Maximum number of papers (10-30, default: 30)
year_from number No Minimum publication year (inclusive). Experimental – see Known limitations.
year_to number No Maximum publication year (inclusive). Experimental – see Known limitations.

Example usage:

Search for recent papers on transformer architectures in NLP from 2023 onwards

Known limitations (year filtering): The year_from / year_to filters are still experimental. The pilot search stage currently does not apply the year filter, so some papers outside the specified range may still appear in results. Full support is tracked in Litra.ai issue #1068. As a workaround, you may need to post-filter the returned papers by their year field.

search_author

Search academic papers by author name.

Parameter Type Required Description
name string Yes Author name
limit number No Maximum number of papers (1-50, default: 20)

Example usage:

Find papers by Yoshua Bengio

check_credits

Check your Litra.ai credit balance and subscription plan. No parameters required.

Pricing & Rate Limits

API access requires a paid Litra.ai subscription (Mini or above). Each search consumes credits from your existing subscription pool.

Plan Rate Limit
Mini 10 requests/min
Standard 30 requests/min
Pro 60 requests/min
Max 120 requests/min

See litra-ai.com/pricing for plan details and pricing.

Response Language

All API responses — including paper titles, summaries, and research overviews — are returned in English only.

This is an intentional design choice for the MCP server and public API:

  • LLM accuracy: Large language models perform reasoning, analysis, and tool use more reliably in English. Returning structured data in English ensures the highest quality when AI agents process search results for downstream tasks (e.g., literature reviews, citation analysis, research synthesis).
  • Token efficiency: English responses consume fewer tokens than translated equivalents, reducing both latency and cost for LLM-based workflows.
  • No multilingual plans for the API: This MCP server is designed specifically for AI agent consumption. There are no plans to add other response languages. If you need Japanese or other languages, use the Litra.ai web interface directly, which provides full Japanese support including translated titles and summaries.

If your AI workflow requires output in a specific language, the AI client can translate the English response as a post-processing step — this is more reliable than asking the API to translate, since the LLM can adapt the translation to your specific context.

Troubleshooting

"LITRA_API_KEY environment variable is required"

Set the LITRA_API_KEY environment variable in your MCP client configuration. See the Setup section for examples.

"Invalid API key"

Your API key may be incorrect or revoked. Generate a new key at litra-ai.com/account.

"Insufficient credits"

Your credit balance is too low. Top up at litra-ai.com/account.

"Paid subscription required"

API access requires a paid plan (Mini or above). Subscribe at litra-ai.com/pricing.

"Rate limit exceeded"

You've exceeded your plan's rate limit. Wait a moment and try again, or upgrade your plan for a higher limit.

Development

git clone https://github.com/akkylab/litra-paper-search-mcp.git
cd litra-paper-search-mcp
npm install
npm run build

To test locally with Claude Code:

claude mcp add litra-paper-search -- node /path/to/litra-paper-search-mcp/dist/index.js

License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选