About Scholarly
Scholarly is an MCP server published by adityak74 in the Developer Tools category: a MCP server to search for accurate academic articles.
The repository has 186 stars and 27 forks, with the last commit a month ago. Recent commit activity is the strongest signal that reported issues will get attention.
Install
git clone https://github.com/adityak74/mcp-scholarlyThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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Static checks derived from the repository 4 days ago. Heuristics on the source, not an audit.
- ✓README presentThe repository ships documentation.
- ✓License declaredUsable under a stated license.
- ✓Tests presentA test suite exists in the repository.
- ✓Dependencies pinnedA lockfile pins dependency versions.
- ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
- !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.
README
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 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).

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
or if you are using Docker
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:
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publish
Note: 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
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 "<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 = 60
Notes 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.
README fetched from the repository 4 days ago. The original is authoritative.
