Memori MCP

Memori turns stateless agents intostateful systemsby providing structured, persistent memory that works across sessions and workflows.
- Persistent state beyond prompts— Most agents rely on prompt context and lose state between runs. Memori providesdurable, structured memoryso agents can retain facts, decisions, and outcomes over time.
- Memory from execution (not just natural language)— Traditional systems extract memory from chat. Memori builds memory fromagent execution itself— including tool calls, decisions, and results. This enables trueagent-native memory, not just conversational recall.
- Lower cost, higher accuracy— Instead of expanding prompt context, Memori retrieves only what matters.

- Significantly reduced token usage
- Faster responses
- Improved accuracy vs long-context approaches

Memori isstate infrastructure for production agents— enabling persistent memory, efficient retrieval, and structured context across both natural language and agent execution.

Memori was evaluated on the LoCoMo benchmark for long-conversation memory and achieved81.95% overall accuracywhile using an average of1,294 tokens per query. That is just4.97% of the full-context footprint, showing that structured memory can preserve reasoning quality without forcing large prompts into every request.

Compared with other retrieval-based memory systems, Memori outperformed Zep, LangMem, and Mem0 while reducing prompt size by roughly67% vs. Zepand lowering context cost by more than20x vs. full-context prompting.

Given the user message:"I prefer Python and use uv for dependency management."
- Agent callsmemori_recallwith the user message asquery
- Agent composes a response using any returned facts
- Agent sends the response to the user
- Agent callsmemori_advanced_augmentationwith theuser_messageandassistant_response

On a later turn like"Write a hello world script", the agent recalls the Python + uv preference and personalizes its response.

Export these in your shell or replace the placeholders directly in your config:

export MEMORI_API_KEY="your-memori-api-key" export MEMORI_ENTITY_ID="user_123" export MEMORI_PROCESS_ID="my_agent" # optional

session_idis derived automatically as<entity_id>-<UTC year-month-day:hour>. You do not need to provide it.

After configuring your client, verify the setup:

- MCP server shows as connected and healthy in your client UI
- Tools list includesmemori_recall,memori_recall_summary,memori_compaction, andmemori_advanced_augmentation
- Calls return non-401 responses
- memori_recallreturns memories for known entities
- memori_advanced_augmentationaccepts durable user/assistant turn data

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