Hosted + Local Agent Memory
Persistent memory for AI agents, without inventing your own stack.
memnode gives agents long-term memory through a hosted API or a local MCP server. You get inspectable recall, provenance, scoped tokens, and shared tenants instead of stitching memory together from prompts and vectors by hand.
Use it for coding assistants, support agents, and research workflows that need durable recall, visible lineage, and a clean correction path across sessions.
When an agent recalls the wrong thing, you need the source, the correction chain, and the current winning memory. That is the real wedge, not just "persistent memory."
- Sign up with Supabase Auth and create an account.
- Provision one hosted tenant through the control plane.
- Create a scoped API token and call the Rust data plane over HTTP.
Typed provenance
Memories carry observed, reported, inferred, or hypothesized status instead of collapsing into one flat blob.
Hosted tenants
Provision a shared hosted tenant in the dashboard, mint API tokens, and keep quota and billing in one place.
Local MCP stays
The hosted product does not replace local usage. You can still run `memnode mcp` over stdio on your own machine.
Rust data plane
A signed-control-plane path, multi-tenant registry, and hot-path token cache keep hosted latency practical.
Example Shapes
Three concrete ways teams use memnode
Conversational assistant
Persist user preferences and past turns across restarts using the standard recall -> answer -> record loop.
Coding assistant
Store project conventions as typed entities instead of free-form notes, then recall them as structured context.
Research agent
Track claims with explicit provenance so later answers can separate reported facts from inferred conclusions.
Start free, keep local in reserve
The hosted SaaS is for fast onboarding, quota-managed tenants, and shared team workflows. The local mode stays available when you need offline or self-managed memory instead.
Latest writings
All articles →7 min read
Mem0 Pricing & Free Tier Limits (2026): Plans, the Retrieval-Call Ceiling, Zep & Letta Cost
Mem0's free tier is 10,000 memory-add requests but only 1,000 retrieval requests a month - and Mem0 meters requests, so retrievals (about...
10 min read
The Consolidation Loop: How Agents Turn Context Into Durable Memory
A pattern is hardening across long-running agents in 2026: every N actions, pause and consolidate the working context into durable memory...
10 min read
Context Bleed: Why Long-Running Agents Need Per-Project Memory Isolation
When one agent works across many projects, its memory bleeds: a convention from project A surfaces in project B, a stale credential reapp...
11 min read
Stop Gluing Three Databases Together for Agent Memory
The typical 2026 agent-memory stack is a vector database for similarity, a graph database for relationships, a relational store for state...
10 min read
Context Engineering for AI Agents: Memory Is the Half Nobody Automates
Context engineering replaced prompt engineering as the 2026 buzzword, but most of the effort goes into sliding windows and summarization....
11 min read
Is RAG Dead for Agents? Retrieval vs Memory in 2026
The "RAG is dead" claim is loud in 2026 and overstated. Naive top-k retrieval over static chunks is the wrong tool for agent memory, but...