past.dev
past.dev is a long-term memory API for developers building AI agents and applications. Applications send timestamped text from conversations, email, meetings, support records, CRM notes, and documents; the service derives memories and returns ranked results with dates and excerpts from the source data. Its API supports ingestion, batch ingestion, recall, deletion, project and identity management, audience-based access controls, and webhooks. Developers can connect through JSON endpoints or authenticated Model Context Protocol servers, and install companion plugins for Claude Code, Codex, Cursor, JetBrains IDEs, and Hermes Agent. The managed cloud service offers a console for API keys, usage, and request logs; enterprise deployments can run in a customer's AWS, Google Cloud, or Azure account. It is aimed at software teams adding persistent, source-grounded memory to AI agents and other applications.
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claude-mem
claude-mem is an offline-first cloud memory for AI agents, built around an open source engine and a cloud sync layer that links agent memory everywhere through one private MCP link. It is designed so coding agents and AI assistants do not start from zero every session, every machine, or every editor. claude-mem takes notes while an agent works, capturing decisions, fixes, dead ends, environment notes, architecture choices, and other structured observations in a temporal database. CMEM Cloud then mirrors that local memory behind a private Model Context Protocol endpoint, allowing any compatible agent or IDE to read and write the same memory across tools such as Claude Code, Cursor, Windsurf, OpenCode, Codex CLI, Gemini CLI, and VS Code. It works locally first, with or without a network, while keeping memory synchronized when cloud access is available.
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Qdrant
Qdrant is a high-performance, composable vector search engine built in Rust for production-grade semantic, hybrid, and agentic workloads.
Combine dense vectors, sparse vectors, metadata filters, multi-vector representations, and custom scoring as primitives at query time. Written in Rust for memory efficiency, SIMD optimization, and predictable performance without garbage collection pauses. No wrappers, no bolt-ons, no legacy compromises — just a custom HNSW implementation and storage engine built specifically for vector workloads.
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Hindsight
Hindsight is an agent memory system built to create smarter AI agents that learn over time instead of starting every conversation from zero. Most agent memory systems focus on recalling conversation history, but Hindsight is focused on making agents learn, not just remember. It gives AI agents persistent long-term memory using biomimetic data structures, helping them retain facts, recall relevant context, and reflect on experience as part of reasoning. Hindsight is designed for agents that need to understand who a user is, what has been discussed, what preferences have emerged, what decisions were made, and how behavior should adapt across sessions. It provides three core operations: retain, recall, and reflect. Retain stores new information, recall retrieves the right memories when needed, and reflect helps agents synthesize observations, form mental models, and learn from prior interactions.
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