A Model Context Protocol server that provides AI agents with persistent memory capabilities through Mem0, allowing them to store, retrieve, and semantically search memories.
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.
A template implementation of the Model Context Protocol server that integrates with Mem0 to provide AI agents with persistent memory capabilities for storing, retrieving, and searching memories using semantic search.
Provides AI agents with persistent long-term memory capabilities using semantic search. Enables storing, retrieving, and searching memories through three core tools integrated with Mem0 and vector storage.
Automatically records AI conversation turns and code changes to local Markdown files to provide persistent context across chat sessions. It enables AI agents to search history through MCP tools and provides a web viewer for browsing past discussions.
Smart memory for AI agents. Solves the Karpathy problem: memories decay, topics are frequency-weighted, one-time questions don't become obsessions. 7 tools. Zero deps.
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.