The 9 Best MCP Memory Servers in 2026, Compared
Coworker AI compares 9 MCP memory servers, from the reference server, Basic Memory and Mem0 to Graphiti, Zep and Cognee: local, hosted or company-wide.
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Coworker AI compares 9 MCP memory servers, from the reference server, Basic Memory and Mem0 to Graphiti, Zep and Cognee: local, hosted or company-wide.
Coworker AI explains the context graph: a knowledge graph plus decision traces and time, how it differs from a knowledge graph, and how to build one.
Coworker AI explains the context layer: what it is, how it differs from a semantic layer, RAG and knowledge graphs, and how to build, buy or test one.
Zeroset has come out of stealth and raised $5.2 million to build models that give AI agents a constantly updated picture of a company's operations.
Memory is what an agent noted and a plugin replays. Documentation is what you wrote, reviewed and committed. How each loads, and what to write down.
How we built long-term memory for Alyx: why we chose one 8,000-character file over retrieval and knowledge graphs, and how we tested it. The post How we built long-term memory for Alyx: why we chose a file over a knowledge graph appeared first on Arize AI.
AI agents can handle large context windows, yet still forget what happened after a session ends. Memory systems close that gap by preserving useful facts, preferences, relationships, and task state, giving agents continuity beyond a single prompt.
Ten open source AI projects from Indian developers, each lined up against the big tech product it takes on. Laya vs Jev, Munder Difflin vs Muse and Grok Bot.
No single AI agent memory layer is best in 2026. The right one depends on tenant isolation, contradiction handling, where you can run it, and what a retrieval costs, all of which you can check in an afternoon.
Coworker AI explains RAG vs MCP: retrieval fetches knowledge, MCP is a connection standard. They solve different problems and most systems need both.
Coworker AI explains context rot: why model accuracy falls as the context window fills, how to measure it, and why retrieval and a knowledge graph beat volume.
A sourced look at how a16z, Emergence, Wing, Kindred and others are betting on memory, context, and AI agents as coworkers — and where ShogunAI fits.
Maximem Synap's persistent agent memory now integrates with Pipecat. Per-caller persistence, entity resolution, and 92% LongMemEval, 93.2% on LoCoMo accuracy for production voice and multimodal pipelines.
Every new generation of Large Language Models arrives with a bigger context window - and the temptation to use it fully. If the model can read a million tokens, why not feed it everything?
Indepth 2025 review of the best AI memory systems for developers. Compare architectures, features, use cases, and performance
With Google’s release of the Agent Payment Protocol (A2P) last month, the agent ecosystem is maturing.
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