Server data from the Official MCP Registry
Academic papers, reference verification and research data for AI agents.
About
Academic papers, reference verification and research data for AI agents.
Remote endpoints: streamable-http: https://scholarmuse.ai/mcp
Security Report
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
Endpoint verified · Requires authentication · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Found in Source Code
Found by scanning the linked source code. This listing connects to a hosted endpoint, so none of this runs on your machine: it describes what the server software does where it is hosted.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-toplocalai-scholarmuse": {
"url": "https://scholarmuse.ai/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
ScholarMuse MCP
Academic research tools for the AI agent you already use.
ScholarMuse connects AI agents to academic papers, reference verification, research datasets, grants, biological and chemical information, and scientific figure tools through one remote MCP endpoint. It provides access to 50+ research sources; upstream availability varies.
- Website: https://scholarmuse.ai
- Remote MCP: https://scholarmuse.ai/mcp
- Transport: Streamable HTTP
- Authentication: OAuth browser sign-in, with automatic discovery and dynamic client registration. No shared tokens or upstream API keys are included in this repository.
- Docs: https://scholarmuse.ai/docs
- Setup guides: https://scholarmuse.ai/connect
- Privacy: https://scholarmuse.ai/privacy
- Terms: https://scholarmuse.ai/terms
- Support: davie@daviechen.com
This repository contains public connection manifests, documentation and branding for the hosted service. The hosted service implementation is not included.
Gemini CLI
gemini extensions install https://github.com/TopLocalAI/scholarmuse-mcp
Complete the browser sign-in when prompted. If needed, use /mcp auth scholarmuse to start authentication. The extension does not bypass tool confirmation.
Cursor, Claude and other MCP clients
Add https://scholarmuse.ai/mcp as a remote Streamable HTTP MCP server and complete OAuth sign-in. See the client-specific setup guides for exact steps. The root plugin.json and mcp.json implement Agent Plugins 1.0.0; .cursor-plugin/plugin.json and .mcp.json provide Cursor-compatible metadata.
Example requests
- Find recent papers about CRISPR delivery and return their DOIs and source links.
- Check whether these references are real and flag retraction information when available.
- Find NIH or NSF grants related to solid-state batteries.
- Retrieve a protein structure or research dataset and cite its original source.
Start with list_capabilities to inspect available tools and get_balance to check credits. Both are free. Most research data tools are read-only; figure creation and editing create generated assets and consume credits. Ask for explicit user approval before paid figure work.
Pricing and limits
ScholarMuse is a hosted freemium service. Data calls generally cost 1–2 credits; batch verification costs depend on item count. New accounts receive 300 trial credits valid for 30 days, and free accounts receive 30 credits per month. Figure generation costs 100 credits and requires a paid plan or credit pack. Check current pricing and the per-tool costs before use.
If credits are insufficient, the server returns structured details and a top-up link. Do not retry paid calls automatically. Upstream failures and partial results must be surfaced accurately with source attribution.
REST API
Developers may also use the REST API documentation and OpenAPI schema.
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