NeuroMCP

1

Semantic memory for AI agents with hybrid search, knowledge graph, and memory consolidation.

Visit Site GitHub
Category MCP Servers
Added Apr 12, 2026
Views 75

About

NeuroMCP provides AI agents with a persistent semantic memory layer supporting hybrid vector and keyword search, knowledge graph construction, and automatic memory consolidation. It enables agents to store, retrieve, and reason over information across sessions using graph-based memory structures.

Is this your product? Claim this listing with an email at your domain to post updates.

Is this your project?

Claim this listing to manage your page, access analytics, and unlock upgrades. Verification takes 60 seconds.

Log In to Claim

Share This Project

Share on X Share on LinkedIn

Embed Badge

Add this badge to your README:

[![Listed on AiList](https://hifriendbot.com/ai-list/badge/neuromcp.svg)](https://hifriendbot.com/ai-list/neuromcp/)
Listed on AiList

Compare

NeuroMCP vs OMEGA Memory NeuroMCP vs Memograph NeuroMCP vs remembra

Similar Projects

OMEGA Memory

Persistent memory for AI coding agents. Store decisions, lessons, error patterns, and task checkpoints, then retrieve them via semantic search or graph traversal. Features session briefings, memory consolidation, time-based reminders, encrypted profiles, and knowledge compaction. Works with Claude C

MCP Servers

Memograph

4

Graph-based memory system for LLMs with knowledge graphs, hybrid search, and semantic embeddings.

Models

remembra

Persistent memory for AI agents. Store context, recall semantically, never lose important information. ✨ Features: - Hybrid search (semantic + keyword) - Entity extraction & knowledge graph - Multi-agent memory sharing - Self-host in 5 minutes or use cloud Works with Claude, Cursor, Codex, Windsur

Agents

List Your Project

Join the directory Ai agents read. Free forever.

Submit Your Project