"How to search for academic papers using Google Scholar" matching MCP servers:

Enables LLMs such as Claude to search for academic papers and fetch detailed metadata, abstracts, and available full-text content from Semantic Scholar and Crossref. It exposes tools for keyword search, topic search with date filtering, and lookup of individual papers by DOI or Semantic Scholar ID.

Enables LLM clients to search for academic papers and retrieve detailed metadata, abstracts, and full-text content when available from Semantic Scholar and Crossref. It supports querying by keyword or topic with date-range filters and looking up specific papers by DOI or Semantic Scholar ID.

Enables LLMs to search academic papers across Semantic Scholar and Crossref, fetch detailed metadata and abstracts by DOI or paper ID, and filter topic searches by publication year. Results are returned as structured responses usable for natural-language research queries.

Enables LLM agents to search academic literature, explore citation graphs, discover related papers, and export BibTeX using arXiv and Semantic Scholar, with prompts for evidence-grounded related-work summaries.

An MCP server that provides Google Search functionality with automatic API key rotation and intelligent quota management, enabling natural language search queries with advanced filtering options.

Enables semantic search across scientific papers in your Zotero library with hybrid search, incremental indexing, and cross-encoder reranking.

A Model Context Protocol server that enables Claude to perform Google Custom Search operations by connecting to Google's search API.

Enables academic research through one stdio server that searches, reads, and relates papers from a large research index, searches multiple paper providers with PDF retrieval and Markdown conversion, and optionally searches a local Markdown corpus with hybrid retrieval and claim comparison. A unified search tool queries all three sources at once while preserving per-source errors.

Provides AI-powered search and documentation tools using Google Vertex AI or Gemini API with real-time web search grounding, enabling technical queries, code analysis, documentation retrieval, and architecture recommendations to overcome LLM knowledge gaps.

Enables creation and management of academic-paper knowledge bases from PDFs, including ingestion, semantic search with reranking, and document-level retrieval via MCP tools.

Enables locally-first literature research through an MCP host by collecting sources, parsing documents, retrieving evidence, validating citations, and exporting research records in multiple formats.

An MCP server that enables AI models to perform Google Web searches using the Gemini API, complete with citations and grounding metadata for accurate information retrieval. It is compatible with Claude Desktop and other MCP clients for real-time web access.

A Model Context Protocol server that enables LLMs to perform web searches using Google's Custom Search API through a standardized interface.

A comprehensive Model Context Protocol server that provides AI assistants with direct access to Semantic Scholar's academic database, enabling advanced paper discovery, citation analysis, author research, and AI-powered recommendations.

MCP server that enables live web search via Gemini's built-in grounding, returning synthesized answers with source citations through a single web_search tool.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Federated, local-first search for AI agents: one query fans across transcripts, files, a knowledge graph, a vector store, the live web, and YouTube, fused by trust-weighted RRF into one ranked answer. Five modes (grep/lexical/semantic/hybrid/rerank), runs entirely on your machine over MCP.

Free, unlimited web search MCP server using Gemini CLI's Google Search grounding to provide cited, live web results for any AI agent.

CLI-first web and code search for agents, with MCP support for integration with IDEs like Cursor, VS Code, and Claude Code.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Enables AI-powered web searches using Google's Gemini 2.5 models with Google Search Grounding. Supports multiple Gemini models (Flash, Flash-Lite, Pro) with configurable thinking budget and web search capabilities.

Enables deep web search across multiple providers including Google, Bing, Brave, DuckDuckGo, and Perplexity, with support for comprehensive AI-powered research using intelligent multi-engine queries.

An MCP server for searching and downloading academic papers from multiple sources including arXiv, PubMed, bioRxiv, and Sci-Hub, designed for seamless integration with large language models like Claude Desktop.

MCP search and evidence tool for AI agents. Rewrites queries, zooms into source domains, and returns sourced answers with metrics.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.

Provides hybrid search (BM25 + vector) and staleness reporting for local markdown notes, exposing search and indexing tools to AI assistants via MCP.