Memori MCP Server

Memori MCP server — persistent AI memory with recall and augmentation tools. Exposed over MCP by the memori mcp mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.

What it actually does

Memori turns stateless agents into stateful systems by providing structured, persistent memory that works across sessions and workflows.

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

Its toolset

Everything the assistant can do here goes through one of these:

• memori_recall — Start of each user turn
• memori_recall_summary — Session starts, daily briefs, status updates, project overviews
• memori_compaction — After context compaction
• memori_advanced_augmentation — After composing a response
• memori_feedback — When the user flags a memory issue or praises a result
• memori_signup — When the user explicitly asks and provides an email
• memori_quota — When the user asks about usage or quota errors appear
• Property — Value
• Server — Memori MCP
• Endpoint — https://api.memorilabs.ai/mcp/
• Transport — Stateless HTTP
• Auth — API key via request headers

Adding it to your client

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

Configuration

You will need 3 environment variables: MEMORI_API_KEY, MEMORI_ENTITY_ID, MEMORI_PROCESS_ID. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

• A Memori API key from app.memorilabs.ai - An entity_id to identify the end user (e.g. user_123) - An optional process_id to identify the agent or workflow (e.g. my_agent) Export these in your shell or replace the placeholders directly in your config: ---

When to reach for it

Among the knowledge and memory options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Memori MCP's toolset — memori_recall, memori_recall_summary, memori_compaction and 11 more — is a fair guide to whether it matches your workflow. It is maintained by memorilabs; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against Memori MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Caveats

• It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
• With 14 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch Memori MCP.
• Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
• MCP clients confirm each tool call by default. Leave that on until you have watched what the memori mcp mcp server does with a few real requests.