Scientific research · MCP server
Scholar Sidekick: MCP server, setup and security
Scholar Sidekick is an open-source MCP server that lets an AI agent resolve scholarly identifiers and format citations or export bibliographic records. Its repository has 11 stars and its last commit is from October 15, 2026 and it is licensed under MIT.
| Adoption (stars) | 10/40 | |
|---|---|---|
| Maintenance | 30/30 | |
| Framework (licence, registry, official) | 20/30 |
What Scholar Sidekick does
According to its repository: “Resolve scholarly identifiers (DOI, PMID, ISBN, arXiv and more) to CSL JSON, format citations in thousands of styles, or export to BibTeX, RIS or EndNote.”
An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Scholar Sidekick is listed under Scientific research, a category of 35 servers in the directory, where it ranks #25 by stars.
Topics declared by the repository: academic, arxiv, bibliography, bibtex, citations, claude.
Installing and connecting Scholar Sidekick
Distribution modes declared in the official MCP registry:
- npm package (Node.js, usually started with
npx) - remote server (streamable-http): you connect to it by URL, with nothing to install locally
Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: TypeScript. Listed systems: macOS, Windows, Linux.
Security: what to check
An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.
None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Scholar Sidekick. That does not replace reading the code.
Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.
Project activity and maintenance
Created on February 13, 2026, the mlava/scholar-sidekick-mcp repository has 11 stars and 0 forks, with 0 open issues. It has more stars than 28% of the servers in the directory. It received changes this month. Version published in the registry: 0.8.13 (October 15, 2026).
Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.
Verdict
Scholar Sidekick is a reasonable choice; check the points below before connecting it.
Strengths
- Active project: recent commit
- Listed in the official MCP registry
- Usable remotely, without installation
- Permissive licence (MIT)
Limitations
- Few visible users
Alternatives
- Zotero MCP (54yyyu)5.5K ★
- ToolUniverse1.8K ★
- Idea reality MCP828 ★
- Research toolkit299 ★
- Paper preflight100 ★
- OmniSeek95 ★
Learn more
Frequently asked questions
How do I install Scholar Sidekick?
Scholar Sidekick is distributed as npm package (Node.js, usually started with npx) and a remote server. Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of mlava/scholar-sidekick-mcp.
Is Scholar Sidekick free?
The code is published under the MIT licence and can be used free of charge.
Is Scholar Sidekick safe?
No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.
Is it an official server?
Nothing says so: it is a project published by mlava on GitHub. Check who maintains it before giving it access.
What are the alternatives to Scholar Sidekick?
In the same category: Zotero MCP (54yyyu), ToolUniverse, Idea reality MCP, and Research toolkit. Zotero MCP (54yyyu) and ToolUniverse score higher on our grid.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score