"PubMed Biomedical Literature Search" matching MCP servers:

Enables biomedical research workflows via MCP, including experiment and document search, PDF text extraction, evidence retrieval, and validation with provenance tracking.

Enables indexing and searching a local library of electrical-engineering PDFs by topic and intent, re-reading cited physical pages for verification, incrementally syncing directories, and producing OpenAlex-based daily literature digests as local Markdown reports with traceable sources.

Enables local literature workflows by searching arXiv, retrieving paper metadata, downloading and parsing PDFs, and retrieving page-cited body evidence for Q&A. It also exposes usage resources and templates for searching, analyzing, and summarizing papers via stdio MCP.

Enables local-first, versioned evidence retrieval from papers without loading the whole library into a conversation, with optional Zotero, writing, fixed-commit code, and experiment record integration returning bounded excerpts and page images.

An academic paper management tool that enables multi-source research searching, batch PDF analysis, and the generation of comprehensive, cross-literature reviews. It features intelligent token compression and quality evaluation to streamline the literature review workflow for researchers.

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.

Enables an AI assistant to search scientific literature across OpenAlex and Semantic Scholar, download supported Elsevier and Springer Nature full texts, and build a local searchable index so questions can be answered with citations to original paper passages. It runs locally over stdio with CPU-based embeddings and needs no Qdrant account, Docker, GPU, or LLM API key of its own.

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

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

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.

Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.

Enables SDK and MCP clients to perform repository code search and retrieval, inspect current source and related evidence, and optionally use semantic search, reranking, and web sources while keeping the calling agent in control.

MCP server for searching files on macOS by name or content using semantic and lexical search, providing file paths and line numbers for agents to read from.

A self-hosted, MCP-native web-search backend for AI agents that provides meta-search, clean extraction, RAG with citations, and GitHub project selection.

Enables web search and AI-summarized answers via an x402-gated gateway, with options for structured results or enriched summaries, accessible as an MCP server.

Enables local, read-only keyword search across past Claude Code, Codex, Gemini CLI, and ChatGPT conversations plus markdown notes, with exact source citations and context retrieval.

Enables AI agents to run semantic search over local Obsidian or Markdown vaults, returning notes ranked by meaning with paths, headings, scores, and snippets, and to trigger incremental reindexing of changed notes. Everything runs on the user's own machine, so no note content leaves it.

Enables semantic search over personal Markdown journal entries by indexing them with Ollama embeddings into a SQLite vector store and exposing retrieval through a Streamable HTTP MCP endpoint at /mcp.