From the Dakera team

Product updates, engineering deep-dives, and developer guides from the people building Dakera.

8 posts

Memory infrastructure

Agent architecture

8 articles

All 8 Engineering 0 Analysis 0 Tutorial 0 Benchmarks 0 Product 0 Launch 0

Latest Post

Analysis 2026-05-13 12 min read

Best AI Agent Memory Frameworks in 2026: Compared and Ranked

Compare the top AI agent memory frameworks — Dakera, Mem0, Letta, Zep, and Hindsight. Benchmarks, architecture, deployment model, and when to use each.

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Tutorial 2026-05-13 7 min read

Dakera MCP Memory Server: Setup Guide for Claude, Cursor, and Windsurf

Step-by-step guide to installing and configuring Dakera as a persistent MCP memory server for Claude Desktop, Claude Code, Cursor, and Windsurf. Docker setup, MCP config, and first recall in under 10 minutes.

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Engineering 2026-05-07 9 min read

Why Rust for AI Memory: Performance, Safety, and a Self-Hosted Server That Fits in 44 MB

Most agent memory systems are Python services that need Docker Compose, Redis, and an external embedding API before you can store a single memory. Dakera is a single Rust binary. Here is why the language choice matters for an always-on memory server.

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Engineering 2026-05-07 5 min read

Dakera as an MCP Memory Server: 83 Tools for Persistent Agent Memory

Dakera ships a native MCP server with 83 tools — store, recall, search, and manage persistent memory from any MCP-compatible agent, host, or IDE without writing a single API call.

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Benchmarks 2026-05-07 9 min read

How We Benchmark Memory: Dakera on LoCoMo

A complete breakdown of Dakera's 87.6% LoCoMo score — the four question categories, the methodology behind each, where temporal inference still has room to improve, and how to run the evaluation against your own instance.

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Product 2026-05-07 7 min read

What's Open in Dakera's Open Core — SDKs, CLI, and MCP Are MIT. The Engine Is Not.

The exact breakdown: SDKs, CLI, and MCP server are MIT-licensed on GitHub. The memory engine and dashboard are proprietary. What "open at the edges, closed at the core" means in practice.

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Launch 2026-05-06 6 min read

Introducing Dakera: Production Memory Infrastructure for AI Agents

We're launching Dakera: a single Rust binary that gives your AI agents persistent memory, hybrid retrieval, knowledge graphs, and built-in embeddings — with no external services required.

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Engineering 2026-05-06 8 min read

How Agent Memory Actually Works: Hybrid Retrieval and Importance Decay

A technical look at the retrieval engine inside Dakera — how we combine HNSW vector search with BM25 full-text search, why naive cosine similarity fails for agent workloads, and how importance decay keeps recall sharp over time.

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Engineering deep-dives, benchmark updates, and developer guides — delivered when we ship something worth reading.