mcp-scholarly MCP server

A MCP server to search for accurate academic articles. More scholarly vendors will be added soon.

Search tools

• `search-arxiv` — arXiv search (no key needed)
• `search-google-scholar` — Google Scholar via the `scholarly` library (free proxy pool)
• `search-google-web` — Google web search via the SerpBase API. Optional; only registered when `SERPBASE_API_KEY` is set. Get a key at https://serpbase.dev/dashboard/api-keys (free tier available).

Components

Tools

The server implements one tool:

• search-arxiv: Search arxiv for articles related to the given keyword.
  • Takes "keyword" as required string arguments

Quickstart

Install

Claude Desktop

On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`

On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

Development/Unpublished Servers Configuration

"mcpServers": {
    "mcp-scholarly": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly",
        "run",
        "mcp-scholarly"
      ]
    }
  }

Published Servers Configuration

"mcpServers": {
    "mcp-scholarly": {
      "command": "uvx",
      "args": [
        "mcp-scholarly"
      ]
    }
  }

or if you are using Docker

Published Docker Servers Configuration

"mcpServers": {
    "mcp-scholarly": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "mcp/scholarly"
      ]
    }
  }

Installing via Smithery

To install mcp-scholarly for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install mcp-scholarly --client claude

Development

Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:

uv sync

2. Build package distributions:

uv build

This will create source and wheel distributions in the `dist/` directory.

3. Publish to PyPI:

uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

• Token: `--token` or `UV_PUBLISH_TOKEN`
• Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging

experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via `npm` with this command:

npx @modelcontextprotocol/inspector uv --directory /Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly run mcp-scholarly

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

Using with zorp

zorp needs a search-capable MCP tool

before `validate` will run. This server satisfies that check, because zorp

matches on a search verb in the tool name and these tools are called

`search-arxiv` and `search-google-scholar`.

zorp-agent --yes \
  --mcp "stdio:scholarly:uv:run:mcp-scholarly" \
  validate ""

Or configure it once, so every run picks it up:

# .zorp/mcp.toml
[[server]]
name = "scholarly"
transport = "stdio"
command = "uv"
args = ["run", "mcp-scholarly"]
trust = "sandbox"
timeout_secs = 60

Notes measured against zorp's transport, not assumed:

• `search-arxiv` answers in about 1 second. zorp's default stdio read

budget is 30 seconds, so the default is comfortable. `timeout_secs = 60`

above is headroom for `search-google-scholar`, which goes through

`scholarly` and a free proxy pool and is far less predictable.

• Logging goes to stderr. Nothing but JSON-RPC reaches stdout, which is

what zorp's newline-delimited framing requires.

• An empty keyword comes back as an MCP tool error rather than an empty

result set. zorp cares about that distinction: a failed search that

looks like "no prior work" would put a wrong novelty score into an

evidence record.

• arxiv returns best-effort matches for any query, including nonsense, so

a non-empty result set is not by itself evidence that prior work exists.

The tool description says so, since that is the text the model reads.