About ScholarMuse
ScholarMuse is a hosted research MCP service for AI agents, bringing academic literature, reference checks, datasets, grants, and scientific information together. It connects to more than 50 research sources through a remote endpoint, with OAuth sign-in.
Key features
- 01Search academic papers and research sources
- 02Verify references and identify retraction information
- 03Find grants and research datasets
- 04Access biological and chemical information
- 05Create and edit scientific figures
Use cases
- 01Find recent papers and source links on a topic
- 02Check citations before including them in a report
- 03Locate grants related to a research area
- 04Retrieve datasets or protein structures with sources
MCP support
ScholarMuse provides a remote Streamable HTTP MCP endpoint at https://scholarmuse.ai/mcp. MCP clients authenticate through OAuth and can inspect tools with list_capabilities.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://scholarmuse.ai/mcpclaude mcp add --transport http toplocalai-scholarmuse https://scholarmuse.ai/mcp{"mcpServers":{"toplocalai-scholarmuse":{"type":"http","url":"https://scholarmuse.ai/mcp"}}}Open in Cursor{"servers":{"toplocalai-scholarmuse":{"type":"http","url":"https://scholarmuse.ai/mcp"}}}Open in VS Code{"mcpServers":{"toplocalai-scholarmuse":{"type":"http","url":"https://scholarmuse.ai/mcp"}}}{"mcpServers":{"toplocalai-scholarmuse":{"serverUrl":"https://scholarmuse.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEScholarMuse 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: [email protected]
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.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.