Sciverse Skills

{
  "mcpServers": {
    "sciverse": {
      "command": "npx",
      "args": ["-y", "sciverse-mcp-server"],
      "env": {
        "SCIVERSE_API_TOKEN": "sv-..."
      }
    }
  }
}

# 一键安装 Agent Skill（推荐给支持 npx skills 的环境）

# 1) 从官方安装
npx skills add https://sciverse.space

# 2) 设置 Token
export SCIVERSE_API_TOKEN=sv-xxx

# 适用任意 OpenClaw 兼容客户端
clawhub install sciverse

# 可选：从 ClawHub Skill 页面选择客户端与填写 Token
#   https://clawhub.ai/sciverse/academic-retrieval

claude /plugin marketplace add https://github.com/opendatalab/Sciverse-Agent-Tools
claude /plugin install sciverse

# 配套安装 MCP 服务
npm install -g sciverse-mcp-server
export SCIVERSE_API_TOKEN=sv-...

git clone https://github.com/opendatalab/Sciverse-Agent-Tools.git
cd Sciverse-Agent-Tools

# 用户级
cp -r skill-claude-code ~/.claude/skills/sciverse

# 或项目级
cp -r skill-claude-code .claude/skills/sciverse

# 同样需要 sciverse-mcp-server
npm install -g sciverse-mcp-server
export SCIVERSE_API_TOKEN=sv-...

# Python
pip install sciverse

# TypeScript / Node.js
npm install sciverse

import asyncio
from sciverse import AgentToolsClient

async def main():
    async with AgentToolsClient(
        base_url="https://api.sciverse.space",
        token="<TOKEN>",
    ) as c:
        r = await c.semantic_search(query="Transformer attention mechanism")
        for hit in r["hits"][:3]:
            print(hit["title"], hit["score"])

asyncio.run(main())

import { AgentToolsClient } from "sciverse";

const c = new AgentToolsClient({
  baseUrl: "https://api.sciverse.space",
  token: process.env.SCIVERSE_API_TOKEN!,
});

const r: any = await c.semanticSearch({ query: "Transformer attention mechanism" });
r.hits.slice(0, 3).forEach((h: any) => console.log(h.title, h.score));

from anthropic import Anthropic
from sciverse import ANTHROPIC_TOOLS

client = Anthropic()
msg = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=2048,
    tools=ANTHROPIC_TOOLS,
    messages=[{"role": "user", "content": "Find a few papers on Transformers"}]
)

import OpenAI from "openai";
import { OPENAI_TOOLS } from "sciverse";

const openai = new OpenAI();
const resp = await openai.chat.completions.create({
  model: "gpt-4o",
  tools: OPENAI_TOOLS as any,
  messages: [{ role: "user", content: "Find a few Transformer papers" }],
});