Enhance AI agents with context-aware capabilities by managing memory storage efficiently through the MCP server, ensuring enterprise-grade security and scalability.
Retrieve comprehensive context from all memory systems using semantic search to enhance AI assistant capabilities in retaining short-term, long-term, and episodic memory.
Retrieve all available conversational AI agents from the ElevenLabs MCP Server to identify and select appropriate agents for text-to-speech and audio processing tasks.
Enables AI agents to manage n8n workflow automation instances through tools for workflow CRUD operations, execution monitoring, and webhook triggering. It facilitates programmatic interaction with n8n instances via the n8n API with AI-optimized descriptions and error handling.
Enables AI agents to store, retrieve, and manage contextual knowledge across sessions using semantic search with PostgreSQL and vector embeddings. Supports memory relationships, clustering, multi-agent isolation, and intelligent caching for persistent conversational context.
Enables AI agents to store, retrieve, and connect information in a Neo4j graph database as persistent memory, with semantic relationships, natural language search, and temporal tracking across conversations.