Skip to main content

Model Context Protocol (MCP)

MCP The memanto-mcp package exposes Memanto’s memory primitives — remember, recall, answer, and friends — as Model Context Protocol tools, so any MCP-compatible client can plug into long-term memory in a single config line.
One Moorcheh API key → typed semantic memory shared across every agent that uses the namespace, with sub-90 ms retrieval, conflict detection, and zero ingestion latency.

Universal

Works with every MCP host: Claude Desktop, Cursor, Windsurf, Cline, Continue, Goose, Codex, and custom agents using the MCP SDK.

Zero glue code

No client code, no vector DB. Add one JSON block to your client’s config and the agent gets 7 memory tools.

Typed memory

13 memory types (fact, preference, decision, goal, instruction, …) with confidence + provenance — built for LLM tool-selection.

Shared namespace

Different clients pointed at the same agent_id share one memory. Remember in Claude Desktop, recall in Cursor.

How It Works

The server runs locally next to your MCP host. On the first tool call it activates a Memanto session (auto-creating the agent if needed) and reuses it across the conversation. Sessions auto-renew before expiry, so long-running MCP connections never hit a session-expired error mid-turn.

Prerequisites

  • Python 3.10+
  • A Moorcheh API key (free tier: 100K ops/month)
  • Any MCP-compatible client

Install

This installs the memanto-mcp console script that every client below launches over stdio.

Quickstart

Pick your client. The JSON shape is identical across most hosts — only the config file path changes.
1

Open the config file

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
Or use Settings → Developer → Edit Config.
2

Add the Memanto server

3

Restart Claude Desktop

Ask Claude to “remember that I prefer concise answers”. Tomorrow, in a brand-new chat, ask “what do I prefer?” — the answer comes from Memanto.
The first call auto-creates the MEMANTO_DEFAULT_AGENT_ID namespace and activates a session. Every subsequent call (in any client pointed at the same agent) reuses the same persistent memory.

Available Tools

The server registers 7 memory tools by default. Set MEMANTO_EXPOSE_ADMIN=true to also expose 4 agent-management tools.

Memory tools (always on)

Agent admin tools (opt-in)

Enabled when MEMANTO_EXPOSE_ADMIN=true:
fact, preference, goal, decision, artifact, learning, event, instruction, relationship, context, observation, commitment, error.See the Memory Types Reference for guidance on picking the right type.
explicit_statement, inferred, corrected, validated, observed, imported.Use explicit_statement when the user said it directly, inferred when you deduced it, and corrected when overriding an earlier wrong memory.
Each memory hit from recall / recall_recent / recall_as_of / recall_changed_since carries its trust and provenance metadata:
  • id, title, content, type, confidence, score, created_at, tags
  • status — lifecycle state; always active for stored memories.
  • source — who wrote the memory: user, agent, the connected MCP client’s identity (e.g. cursor, codex), or the uploaded file name.
  • source_ref — pointer to the original record within that source (e.g. tool-call or migration id). null when not set.
  • provenance — how the memory was obtained (explicit_statement, inferred, …).

Configuration

All configuration is via environment variables (load order: process env → .env file in the working directory). Most clients let you set these inside the env block of the MCP server entry. CLI flags override env vars:

Running over HTTP / SSE

For remote clients or multi-process setups, run the server over a network transport:
The server authenticates upstream to Moorcheh with your API key, but does not authenticate inbound MCP clients. For production, pair it with a reverse proxy that enforces auth (e.g. mTLS, OAuth, or a shared bearer token).

Programmatic Embedding

Wiring the server into a larger Python process or custom MCP host:
Useful when you want to combine Memanto with a domain-specific MCP toolset in one process.

Sharing Memory Across Clients

Point multiple clients at the same MEMANTO_DEFAULT_AGENT_ID and they share one persistent memory namespace:
A preference stored in Claude Desktop is now recallable from Cursor on the next tool call — Moorcheh’s no-indexing search means the memory is queryable the millisecond it’s written.

Troubleshooting

Next Steps

Memory Types Reference

Learn which memory type to pick for each piece of information.

Agent Management

Create, activate, and switch Memanto agents.

Remember API

The REST endpoint the remember MCP tool wraps.

Recall API

The REST endpoint the recall MCP tool wraps.

Links