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Science AI MCP Server

by SelfPy

Research workflow tools for paper screening, duplication checks, journal selection, gap finding, peer review, and article writing.

Install Science AI MCP Server

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "selfpy-science-ai-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "science-ai-mcp-server"
      ],
      "env": {
        "SCIENCE_AI_API_KEY": "YOUR_VALUE_HERE",
        "SCIENCE_AI_BASE_URL": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y science-ai-mcp-server

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 1mo ago.

Overview

SelfPy/science-ai-mcp-server MCP server exposes Science AI Journal research workflows through MCP clients such as Claude Desktop, Cursor, and Cline. It covers local paper pre-checking, publication-duplication searches, journal recommendations, research-gap analysis, AI review, and an Article Writer pipeline. A Science AI Journal API key is required, while some tools use account credits and others are free. Reach for it when an agent needs structured support for evaluating, reviewing, or preparing academic papers.

Use cases

  • Screen a paper abstract before selecting a submission strategy
  • Check a manuscript for possible duplicate publication
  • Rank journals and identify predatory-journal flags
  • Find research gaps and relevant highly cited papers
  • Run an AI review or start an article-writing workflow

Key features

  • Title-and-abstract acceptance tier prediction
  • Cross-source duplicate publication checking
  • Journal ranking across 1,214 venues
  • Research-gap synthesis with citation and recency results
  • AI peer review and Article Writer pipeline controls

Tools6

What Science AI MCP Server lets your agent do. Expand a tool for its parameters.

Self-reported~135 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 2d ago

Recent health check succeeded.

16/17 checks healthy over the last 80d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 9d ago via OSV.dev · science-ai-mcp-server (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars1Stargazers on the source repository.
npm downloads203Package downloads in the last 30 days.
Last commit5mo agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Tools exposed6Callable tools this server registers over MCP.
Directory activity8 viewsConfig copies, upvotes, and views on AllMCPs.

How Science AI MCP Server works

What the SelfPy/science-ai-mcp-server MCP server does

SelfPy/science-ai-mcp-server MCP server brings Science AI Journal workflows into MCP-enabled assistants. It is aimed at researchers and developers building agent-assisted academic workflows, rather than general web search or document storage.

The available functions cover several stages of a publication workflow. A paper can be screened from its title and abstract, checked for possible duplicate publication, matched with journals, and analyzed for research gaps. The server also exposes an AI peer-review pass and controls for the Article Writer pipeline.

How it works

The client launches the package as a local MCP process and passes requests to Science AI Journal using an API key. The configured base URL defaults to the Science AI Journal service and can be changed for staging or self-hosted deployments.

Some operations use local or indexed data rather than an LLM. Paper pre-checking uses FTS5 and returns a predicted acceptance tier from 1 through 5. Duplicate checking searches CrossRef, arXiv, medRxiv, bioRxiv, Unpaywall, and a library containing about 900,000 papers. Journal recommendations use an index of 1,214 venues and include predatory-journal flags.

Other operations consume the caller's Science AI Journal account credits. These include research-gap synthesis, AI review, and Article Writer pipeline operations. The gap tool returns synthesized gaps along with highly cited and recent papers related to a query. The review tool performs a single-agent pass on a prepared prompt.

Setup and configuration

Install and run the SelfPy/science-ai-mcp-server MCP server through npx with Node.js 20 or newer:

config.json
{
  "mcpServers": {
    "science-ai-journal": {
      "command": "npx",
      "args": ["-y", "science-ai-mcp-server"],
      "env": {
        "SCIENCE_AI_API_KEY": "saij_your_key"
      }
    }
  }
}

Create the API key from the Science AI Journal account settings. A free account is required, and the token is shown only once. SCIENCE_AI_API_KEY is required. SCIENCE_AI_BASE_URL is optional and defaults to https://scienceaijournal.com; use it when targeting a supported staging or self-hosted endpoint.

The same MCP server configuration is documented for Claude Desktop, Cursor, and Cline. After changing the configuration, fully quit and reopen the host application so it reloads the server. An unauthorized response generally indicates an invalid, revoked, or expired key. The documented rate limit for find_research_gaps is 10 requests per hour per IP.

Tools and capabilities

  • pre_check_paper: Estimates a paper's acceptance tier from its title and abstract without an LLM.
  • check_duplicate_publication: Cross-references multiple scholarly indexes and the paper library.
  • recommend_journals: Ranks possible journals and marks predatory venues.
  • find_research_gaps: Produces research gaps and related citation and recency results.
  • ai_review_paper: Runs one AI peer-review pass over a prepared prompt.
  • start_writer_pipeline and get_writer_pipeline_status: Start and monitor the Article Writer pipeline.

SelfPy/science-ai-mcp-server MCP server is licensed under MIT. Its free tools do not require LLM usage, while credit-based operations depend on the caller's Science AI Journal account balance.

Reviews

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Frequently Asked Questions about Science AI MCP Server

Run it through npx with `npx -y science-ai-mcp-server` and configure the `SCIENCE_AI_API_KEY` environment variable. Node.js 20 or newer is required.

Yes. The README provides a Claude Desktop configuration, and the same setup is also documented for Cursor and Cline.

It requires a Science AI Journal API key stored in `SCIENCE_AI_API_KEY`. The key is generated from Science AI Journal account settings, and a free account is required.

Pre-checking, duplicate publication checking, and journal recommendations are listed as free. Research-gap finding, AI review, and Article Writer operations use account credits.

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