Community Servers · MODEL CONTEXT PROTOCOL
mcp-scholarly
A MCP server to search for accurate academic articles.
WHAT IT CONNECTS
What mcp-scholarly gives an AI Agent
The source catalog does not include a structured feature list. Review the repository documentation before use.
SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.
README
Repository documentation
A MCP server to search for accurate academic articles. More scholarly vendors will be added soon.
search-arxiv— arXiv search (no key needed)search-google-scholar— Google Scholar via thescholarlylibrary (free proxy pool)search-google-web— Google web search via the SerpBase API. Optional; only registered whenSERPBASE_API_KEYis set. Get a key at https://serpbase.dev/dashboard/api-keys (free tier available).
The server implements one tool:
- search-arxiv: Search arxiv for articles related to the given keyword.
- Takes "keyword" as required string arguments
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Development/Unpublished Servers Configuration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" ] } } ```To install mcp-scholarly for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install mcp-scholarly --client claudeTo prepare the package for distribution:
- Sync dependencies and update lockfile:
uv sync- Build package distributions:
uv buildThis will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publishNote: You'll need to set PyPI credentials via environment variables or command flags:
- Token:
--tokenorUV_PUBLISH_TOKEN - Or username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
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-scholarlyUpon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
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 "<your research question>"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 = 60Notes measured against zorp's transport, not assumed:
search-arxivanswers in about 1 second. zorp's default stdio read budget is 30 seconds, so the default is comfortable.timeout_secs = 60above is headroom forsearch-google-scholar, which goes throughscholarlyand 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.
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