"Google search or related query" matching MCP servers:

Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.

Enables users to import, synchronize, index, and search their conversations from Gemini, Search AI Mode, AI Studio, NotebookLM, My Activity, and related services through MCP clients. It also fetches individual chats from pasted URLs for continuation or project creation, storing local Markdown transcripts and providing SQLite FTS5 full-text search.

Enables agents to run cross-runtime, cross-machine BM25 full-text search over historical conversations from Hermes, Google Antigravity, OpenClaw, Codex, and Claude Code, and to retrieve any past session's full transcript by ID. Queries return only ranked matching snippets, so recall costs no extra tokens or embeddings.

A federation MCP server that sits in front of multiple memory backends and presents a unified search surface to AI agents, allowing a single query to search across knowledge graphs, session history, and web search.

Read-only MCP server that exposes your local Notion backups to AI agents — query databases, read pages, search a backed-up workspace. Offline by default: no LLM calls, no telemetry, no cloud.

Lets users manage master data through natural-language conversations with AI agents, enabling schema creation, record capture, validation, search, and query answering via 16 MCP tools backed by local JSON storage.

Gives your AI persistent memory across conversations. Stores facts automatically, finds them by meaning using hybrid search with query expansion, and organizes everything into topics without manual tagging.

Local MCP server that manages a job search using Markdown files, enabling skills tracking, gap analysis, and offer pipeline management via Claude.

Enables Claude chats to communicate across machines or sessions via shared encrypted rooms, with tools to create, join, send, read, wait, search, and delete room messages.

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.

MCP server that connects any AI to your Obsidian vault. Save articles from your phone, search across notes, build a compounding knowledge base. 15 tools, three transport modes (stdio, HTTP, cloud), zero-install Google Drive OAuth onboarding.

An MCP server that reads all your Claude Code project memory files and exposes them as tools. Lets any Claude instance — in any project, or via Claude.ai — query your full project history and preferences.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

Enables searching Google Scholar with Scholar operators, year ranges, cited-by and all-versions lookups, and retrieving citations in five styles with BibTeX and EndNote export links as structured JSON.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.

Shared memory MCP server for AI coding agents, enabling context sharing across sessions with local SQLite or cloud-based semantic search, compatible with Claude Code and Cursor.

Enables keyword search, filtering, and retrieval of Claude Code memory files, reducing context overhead by fetching only relevant memories on demand.

Enables code agents to persist and recall durable project knowledge — rules, decisions, procedures, learnings and secrets — across sessions at low context cost, with accent-insensitive PT-BR search, scoped per repository/workspace, and secrets that stay out of the model's context.

Enables AI agents to persist facts with tags, sources, and importance in a local SQLite database, retrieve them through hybrid BM25 plus embedding search weighted by retention decay, link or supersede related entries, and review everything in a read-only visual dashboard showing the memory graph and timeline.

Enables AI assistants to query your local browsing history using keyword search, RAG Q&A, and activity stats.

Structured knowledge API for AI agents — fractal knowledge graphs, signal datasets, authority evidence reviews, open problems, and capability specs. Pay-per-query or subscription via Lightning, Stripe, or USDC.

Provides a read-only semantic layer over an Obsidian vault, enabling queries about projects, decisions, tasks, and related notes.

Enables AI assistants to query end-to-end encrypted memories from Cognia workspace via MCP. Supports search, retrieval, and action execution against connected services like Slack, Notion, and GitHub.

Enables AI assistants to query, modify, and reason over OWL/TTL/RDF ontology files using natural language, without needing SPARQL or OWL syntax.

Enables project-scoped agent memory backed by a per-project SQLite index and raw data store, plus a global registry for discovering local memory workspaces. Agents can search summaries, retrieve original records on demand, save new memories, and link related records without sharing memory across projects.

MCP server for Yandex Wiki with full-text search. Read and write pages, comments, attachments, and dynamic tables (grids); optional server-side read-only mode for agents. Docker-ready.

Enables MCP-compatible agents to query beliefs, search documents, and explore reasoning chains from expert-service knowledge bases.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.