A robust server for managing long-term agent memory using Mem0, providing efficient storage and retrieval of agent memories with a lightweight Python-based implementation.
With Memori's MCP server, your agent can retrieve relevant memories before answering and store durable facts after responding, keeping context across sessions without any SDK integration.
With MCP, it can:
Store stable user facts and preferences after answering using the advanced_augmentation tool
Recall relevant memories before answering using the recall tool
Maintain context across sessions us
A Model Context Protocol server that extracts and processes content from PDF documents, providing text extraction, metadata retrieval, page-level processing, and PDF validation capabilities.
A Model Context Protocol server that enables fetching and processing images from URLs, local file paths, and numpy arrays, returning them as base64-encoded strings with proper MIME types.
This server provides a comprehensive integration with Zendesk. Retrieving and managing tickets and comments. Ticket analyzes and response drafting. Access to help center articles as knowledge base.
An advanced integrated MCP server platform that combines 600+ tools and multiple biomedical databases to enable comprehensive information retrieval across molecules, proteins, genes, and diseases for accelerating therapeutic research.
Provides advanced document search and processing capabilities through vector stores, including PDF processing, semantic search, web search integration, and file operations. Enables users to create searchable document collections and retrieve relevant information using natural language queries.
An MCP server that transforms codebases into knowledge graphs using Neo4J, enabling AI assistants to understand code structure, relationships, and metrics for more context-aware assistance.