Search arXiv papers and fetch metadata via @cyanheads/arxiv-mcp-server (npx)

Recipe: Search arXiv papers via MCP

Server: @cyanheads/arxiv-mcp-server v1.2.13 Transport: stdio Launcher: npx -y @cyanheads/arxiv-mcp-server Auth: none (arXiv API is public)

Tools available (4)

Verified trace: arxiv_search

Query: "transformer attention mechanism", max_results=2

Request:

{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"arxiv_search","arguments":{"query":"transformer attention mechanism","max_results":2}}}

Response (structuredContent):

{
  "total_results": 467866,
  "start": 0,
  "papers": [
    {
      "id": "2206.03003v2",
      "title": "Transformer-based Personalized Attention Mechanism for Medical Images with Clinical Records",
      "authors": ["Yusuke Takagi", "Noriaki Hashimoto", ...],
      "abstract": "In medical image diagnosis, identifying the attention region...",
      "categories": ["eess.IV", "cs.CV"],
      "published": "2022-06-07T04:35:22Z",
      "links": { "abstract": "https://arxiv.org/abs/2206.03003v2", "pdf": "https://arxiv.org/pdf/2206.03003v2" }
    },
    {
      "id": "2209.15001v3",
      "title": "Dilated Neighborhood Attention Transformer",
      "authors": ["Ali Hassani", "Humphrey Shi"],
      "categories": ["cs.CV", "cs.AI", "cs.LG"],
      "published": "2022-09-29T17:57:08Z"
    }
  ]
}

Latency: 811ms (includes arXiv API round-trip)

Query syntax

The query parameter supports arXiv's field prefixes:

• ti: (title), au: (author), abs: (abstract), cat: (category), all: (all fields)
• Boolean: AND, OR, ANDNOT
• Example: "au:bengio AND ti:attention AND cat:cs.CL"

Notes

• The response includes both human-readable text (in content[0].text) AND structured data (in structuredContent.papers[]) — use the structured form for programmatic access.
• max_results caps at 50 per call; use start for pagination.
• Cold start is ~4s for npx download; subsequent invocations reuse cache.