Google Scholar academic search, citation tracking, and research discovery
Google Scholar Tools gives AI agents access to academic and scientific literature through a managed google scholar api — the world's largest academic search engine covering research papers, theses, books, conference proceedings, preprints, and court opinions, delivering the citation network depth of a serpapi google scholar integration without requiring a third-party intermediary account.
It acts as a standardized bridge between large language models and scholarly knowledge. Instead of relying solely on training data for academic content, models can retrieve current research, citation networks, and author publication records through a controlled MCP interface — functioning as a comprehensive google scholar search api for AI-powered research workflows.
By integrating Google Scholar Tools, developers enable AI agents to:
• Find scholarly articles by keyword using search_papers — returning titles, authors, publication venue, year, citation count, and abstract snippets • Retrieve the full publication list for any researcher with search_by_author — enabling author profiling and academic influence analysis • Discover papers that cite a given work using get_citations — essential for understanding research impact and finding related literature through the google scholar api citation graph • Narrow searches to specific publication date ranges with filter_by_year — keeping research current or focusing on foundational seminal works
Indispensable for research assistant agents, literature review tools, academic writing assistants, evidence-grounding pipelines, and any AI system that needs to engage with peer-reviewed scientific knowledge through a reliable google scholar search api.
Standardized bridge for real-time model context.
Connect this server to your local or remote agent environment.
{
"mcpServers": {
"mcp360": {
"command": "npx",
"args": [
"mcp-remote",
"https://connect.mcp360.ai/v1/google-scholar/mcp?token=YOUR_API_KEY"
]
}
}
}Technical specifications for the 4 available protocol tools.
filter_by_year tool
Production-ready REST endpoints for custom integrations.
/api/v1/google-scholarcurl "https://connect.mcp360.ai/api/v1/google-scholar" \
-H "Authorization: Bearer YOUR_API_KEY"/api/v1/google-scholar/{tool_name}curl -X POST "https://connect.mcp360.ai/api/v1/google-scholar/filter_by_year" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query": "string",
"year": 1
}'To authenticate, include your API key in the Authorization header using the Bearer scheme. Alternatively, you can use the X-API-KEY header.
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Google Scholar Tools is an MCP server that provides structured access to google scholar tools capabilities through a standardized protocol, enabling AI models to retrieve and process real-time data.
Any model that supports MCP protocol including Claude (via Claude Desktop), GPT-4, Gemini, and open-source LLMs through compatible frameworks.
The server supports OAuth 2.0 authentication with API keys. You'll receive credentials upon registration which can be configured in your MCP client.
Yes, rate limits apply based on your subscription tier. Free tier includes generous limits for development, with higher limits available in paid plans.
Absolutely. Google Scholar Tools is designed for production use with enterprise-grade reliability, security, and performance.
Start building production-ready AI agent integrations in minutes with standardized protocol access.