"Search for the term pHqghUme" matching MCP servers:

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

Exposes an internal engineering knowledge base to AI assistants, allowing users to search and retrieve standards, runbooks, and architecture decisions. It supports RAG-enhanced search, document scraping, and specialized prompts for incident investigation and code reviews.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

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

MCP server for Doubao Search that enables real web search in any MCP client, backed by ByteDance-exclusive Chinese sources and the open web.

Persistent long-term memory for AI coding assistants. Local SQLite, no cloud - 16 MCP tools to store, search, relate, and consolidate typed memories with a confidence lifecycle, hybrid BM25 + semantic search, namespaces, a knowledge graph, and a built-in OS keychain credential vault.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

An intelligent memory MCP server that provides AI applications with semantic search, entity extraction, and knowledge graph capabilities using local Redis caching and optional cloud sync. It enables LLMs to store and retrieve long-term context across sessions with high-performance multi-tier storage.

Provides persistent long-term memory for AI agents through semantic search and automated knowledge graph extraction. It enables agents to store, recall, and reason over facts, preferences, and relationships across multiple conversations and sessions.

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

Enables natural-language semantic search over your own local files through an MCP server, fully offline without API keys or a server daemon, with optional LLM-grounded answers and exact file:line sources.

Enables searching and retrieving documents from a local folder to ground LLM answers in your files.

Provides long-term memory for agents with meaning-based recall, evidence-gated writing, and separate stores per agent mode.

Connect AI assistants to Manticore Search. Execute SQL queries, list tables, get schemas, and fetch documentation. Perfect for building RAG applications and search-powered AI agents.

The Search MCP Server enables seamless integration of network and local search capabilities in tools like Claude Desktop and Cursor, utilizing the Brave Search API for high-concurrency and asynchronous requests.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

Local semantic recall MCP server for citation-integrity workflows. Enables semantic search over a text corpus, returning file paths and page numbers for verification, with 100% local processing using ONNX embeddings and LanceDB.

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.

A high-performance MCP server providing long-term memory storage with semantic and keyword search capabilities, using SQLite and fastembed for sub-200ms queries.

Enables AI coding assistants to semantically search codebases by meaning rather than exact text, with zero external daemons and fully local embeddings. Works out-of-the-box with Claude Code, Gemini CLI, Antigravity, and Cursor.