"Semantic UI" matching MCP servers:

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Turns team chat (Slack, Discord, MS Teams, Mattermost) into a living knowledge base - a typed knowledge graph plus auto-generated wiki - exposed to AI agents through a 28-tool MCP server with semantic search, expert finding, and decision tracing.

Persistent semantic memory for your SQL databases. The name is ironic — it remembers everything.

MCP file cache for AI coding agents. Re-reading an unchanged file costs ~40 tokens instead of the whole file; a changed file comes back as a diff. Adds grep, BM25 search and glob over cached files, atomic edits with dry_run, and token-budgeted batch reads. One local daemon serves every client. No API keys, no GPU. Works with Claude Code, Cursor, VS Code, Codex and OpenCode.

Enables AI assistants to manage memories via the mem9 memory service, supporting memory storage, semantic search, retrieval, update, and deletion across multiple platforms.

Provides seamless access to the ConceptNet semantic knowledge graph, enabling concept lookup, search, relationship discovery, and semantic similarity calculations across multiple languages.

Read-only MCP server that surfaces contradictions in an Obsidian vault's knowledge graph via semantic search and reasoning edges.

Semantic codebase search + persistent working memory for AI code editors. Local, zero-config, MCP. No API key.

MCP Server for local knowledge management. Semantic + keywords + tags

Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.

Semantic search across Claude Code conversations. Hybrid vector + keyword search, fully local, background indexing.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

Project-scoped semantic workspace memory for AI coding assistants. Watches your project files and auto-indexes code and docs into Qdrant using tree-sitter semantic chunking and hybrid search (dense + sparse + RRF)

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 Claude, Cursor, Windsurf, and autonomous agents to save web pages and notes as persistent memories, then search them using full-text keyword matching and semantic vector recall.

Provides semantic search and knowledge graph capabilities for Obsidian vaults using Smart Connections embeddings.

MCP server that gives AI agents persistent, tenant-scoped memory with semantic search and consolidation, using CockroachDB vector indexes and Amazon Bedrock embeddings.

Gives agents a stable interface for durable memory, combining exact, lexical, semantic, and graph search results.

Persistent, graph-based memory for Roo Code via the Model Context Protocol, enabling structured knowledge management with semantic search and context window control.

MCP server for Locus, a local semantic dataspace manager powered by Ollama. It exposes all Locus HTTP endpoints as MCP tools to manage dataspaces, ingest documents, and perform semantic search.