"LMMS" matching MCP servers:

Enables complex problem-solving through multi-modal reasoning, dynamic knowledge graphs, meta-cognitive reflection, and collaborative AI personas.

An MCP server that decides whether each step of an agent requires cheap intuition (System 1) or expensive deliberation (System 2) by learning from experience rather than hand-written rules.

A server that manages conversation context for LLM interactions, storing recent prompts and providing relevant context for each user via REST API endpoints.

A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.

Cognitive memory system for AI agents with 129 MCP tools. Persistent 6-tier hierarchical memory (working→short-term→long-term→semantic), Ebbinghaus forgetting curves, dream consolidation, hybrid retrieval (BM25+RRF), goal tracking, emotional recall, knowledge graphs, and a 26-job consciousness daemon. Works with Claude Code, Cursor, and any MCP client.