"General Search Query" matching MCP servers:

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.

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.

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.

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

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.

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

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

An MCP server that provides graph-aware tools for interacting with Little Big Brain knowledge graphs, enabling search, query, commit, and configuration operations via natural language.

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 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.

A general-purpose MCP server providing web search, persistent memory storage, and secure code execution capabilities. It enables AI agents to search the web, store and retrieve data, and run Python/JavaScript code in sandboxed environments.

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.

Enables AI agents to persist, search, and query shared memories in PostgreSQL through hybrid retrieval, preset answers, and AI-to-AI consultation via MCP.

MCP server for NaN Mesh, enabling AI agents to search entities, cast trust reviews, register agents, post content, and query trust scores from the AI trust network.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Enables AI coding assistants to query and store a team's historical development experience through semantic search, so lessons and decisions persist across conversations.

Enables Claude to search, query, and interact with an Enterprise Knowledge Management System (EKMS). Supports semantic search, knowledge recommendations, relationship graphs, and feedback recording for enterprise knowledge bases.