Model Context Protocol (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

┌──────────────┐    MCP (stdio)    ┌──────────────────┐    HTTPS + API key   ┌─────────────┐
│ Claude / IDE │ ────────────────► │   memanto-mcp    │ ───────────────────► │   Moorcheh  │
│   (client)   │ ◄──────────────── │   (this server)  │ ◄─────────────────── │   Service   │
└──────────────┘   tool calls      └──────────────────┘   no-indexing search └─────────────┘

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

pip install memanto-mcp

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.

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.

Add the Memanto server

{
  "mcpServers": {
    "memanto": {
      "command": "memanto-mcp",
      "env": {
        "MOORCHEH_API_KEY": "mch_xxxxxxxxxxxxxxxxxx",
        "MEMANTO_DEFAULT_AGENT_ID": "my-assistant"
      }
    }
  }
}

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.

Open the config file

Per-user: ~/.cursor/mcp.json
Per-project: .cursor/mcp.json (committable)

Add the Memanto server

{
  "mcpServers": {
    "memanto": {
      "command": "memanto-mcp",
      "env": {
        "MOORCHEH_API_KEY": "mch_xxxxxxxxxxxxxxxxxx",
        "MEMANTO_DEFAULT_AGENT_ID": "cursor-workspace"
      }
    }
  }
}

Reload Cursor

Open the MCP panel and confirm memanto shows up with 7 tools.

Edit ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "memanto": {
      "command": "memanto-mcp",
      "env": {
        "MOORCHEH_API_KEY": "mch_xxxxxxxxxxxxxxxxxx",
        "MEMANTO_DEFAULT_AGENT_ID": "windsurf-workspace"
      }
    }
  }
}

Reload Windsurf via Cascade → MCP Servers → Refresh.

Edit cline_mcp_settings.json (path depends on OS):

Linux: ~/.config/Code/User/globalStorage/cline.cline/settings/cline_mcp_settings.json
macOS: ~/Library/Application Support/Code/User/globalStorage/cline.cline/settings/cline_mcp_settings.json
Windows: %APPDATA%\Code\User\globalStorage\cline.cline\settings\cline_mcp_settings.json

{
  "mcpServers": {
    "memanto": {
      "command": "memanto-mcp",
      "env": {
        "MOORCHEH_API_KEY": "mch_xxxxxxxxxxxxxxxxxx",
        "MEMANTO_DEFAULT_AGENT_ID": "cline-workspace"
      }
    }
  }
}

Edit ~/.continue/config.json:

{
  "experimental": {
    "modelContextProtocolServers": [
      {
        "transport": {
          "type": "stdio",
          "command": "memanto-mcp",
          "env": {
            "MOORCHEH_API_KEY": "mch_xxxxxxxxxxxxxxxxxx",
            "MEMANTO_DEFAULT_AGENT_ID": "continue-workspace"
          }
        }
      }
    ]
  }
}

Edit ~/.config/goose/config.yaml:

extensions:
  memanto:
    type: stdio
    command: memanto-mcp
    envs:
      MOORCHEH_API_KEY: mch_xxxxxxxxxxxxxxxxxx
      MEMANTO_DEFAULT_AGENT_ID: goose-workspace

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)

Tool	When the agent should call it
`remember`	Persist a single fact, preference, decision, goal, or instruction.
`batch_remember`	Persist up to 100 memories in one call (e.g. extracted from a document).
`recall`	Semantic search — always check here before asking the user to repeat stable info.
`recall_recent`	”What did we just decide?” — newest-first, no query needed.
`recall_as_of`	Point-in-time recall — “what did we know on 2025-11-01?”
`recall_changed_since`	Differential recall — “what’s new since I last checked?”
`answer`	RAG: a grounded LLM answer synthesized over the agent’s memories.

Agent admin tools (opt-in)

Enabled when MEMANTO_EXPOSE_ADMIN=true:

Tool	Purpose
`create_agent`	Create a new memory namespace.
`list_agents`	List every agent the API key can see.
`get_agent`	Look up an agent’s metadata.
`delete_agent`	Remove an agent’s local metadata.

Memory types accepted by remember / batch_remember

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.

Provenance values

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.

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.

Variable	Required	Default	Description
`MOORCHEH_API_KEY`	yes	—	Moorcheh API key.
`MEMANTO_DEFAULT_AGENT_ID`	recommended	—	Default agent. When set, tool calls may omit `agent_id`.
`MEMANTO_AGENT_PATTERN`	no	`tool`	Pattern (`support` / `project` / `tool`) used when auto-creating the default agent.
`MEMANTO_AGENT_AUTO_CREATE`	no	`true`	Create the default agent on first use if missing.
`MEMANTO_SESSION_DURATION_HOURS`	no	`6`	Session lifetime in hours (1 – 720).
`MEMANTO_EXPOSE_ADMIN`	no	`false`	Register the 4 agent-management tools.
`MEMANTO_MCP_TRANSPORT`	no	`stdio`	`stdio`, `sse`, or `streamable-http`.
`MEMANTO_MCP_HOST`	no	`127.0.0.1`	Bind host for sse / http transports.
`MEMANTO_MCP_PORT`	no	`8765`	Bind port for sse / http transports.
`MEMANTO_MCP_LOG_LEVEL`	no	`INFO`	Log level. Logs are always sent to stderr.

CLI flags override env vars:

memanto-mcp --transport sse --port 9000 --log-level DEBUG

Running over HTTP / SSE

For remote clients or multi-process setups, run the server over a network transport:

Streamable HTTP (recommended)
SSE (legacy)

memanto-mcp --transport streamable-http --host 0.0.0.0 --port 8765

Point your client at http://your-host:8765/mcp.

memanto-mcp --transport sse --host 0.0.0.0 --port 8765

Older transport, still widely supported.

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:

from memanto_mcp import MCPServerSettings, build_server

settings = MCPServerSettings()  # reads env / .env
mcp = build_server(settings)

# Add your own tools alongside Memanto's, then run.
mcp.run(transport="stdio")

Useful when you want to combine Memanto with a domain-specific MCP toolset in one process. Point multiple clients at the same MEMANTO_DEFAULT_AGENT_ID and they share one persistent memory namespace:

// Claude Desktop
"env": { "MEMANTO_DEFAULT_AGENT_ID": "my-personal" }

// Cursor
"env": { "MEMANTO_DEFAULT_AGENT_ID": "my-personal" }

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

Symptom	Fix
`configuration error: MOORCHEH_API_KEY is required`	Set the env var in your MCP client config’s `env` block.
`Agent '…' does not exist and MEMANTO_AGENT_AUTO_CREATE is disabled`	Re-enable auto-create, or call `create_agent` (admin tools) / `memanto agent create <id>` once.
Tools never appear in the client	Confirm the client supports MCP and the config path matches. Check the client’s MCP log: `memanto_mcp` lines on startup come from this server.
Garbled output in stdio mode	Something on your side is writing to stdout — that channel is reserved for JSON-RPC. Move logs to stderr. The server itself only writes to stderr.
Slow first call	Cold-start cost: SDK import + first session activation. Subsequent calls reuse the live session.
Session-expired errors mid-conversation	The server auto-renews before expiry. If you still see this, bump `MEMANTO_SESSION_DURATION_HOURS`.

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

Overview

Protocols

Frameworks

MCP Integration

Model Context Protocol (MCP)

Universal

Zero glue code

Typed memory

Shared namespace

How It Works

Prerequisites

Install

Quickstart

Available Tools

Memory tools (always on)

Agent admin tools (opt-in)

Configuration

Running over HTTP / SSE

Programmatic Embedding

Troubleshooting

Next Steps

Memory Types Reference

Agent Management

Remember API

Recall API

Overview

Protocols

Frameworks

Documentation Index

​Model Context Protocol (MCP)

Universal

Zero glue code

Typed memory

Shared namespace

​How It Works

​Prerequisites

​Install

​Quickstart

​Available Tools

​Memory tools (always on)

​Agent admin tools (opt-in)

​Configuration

​Running over HTTP / SSE

​Programmatic Embedding

​Sharing Memory Across Clients

​Troubleshooting

​Next Steps

Memory Types Reference

Agent Management

Remember API

Recall API

Model Context Protocol (MCP)

How It Works

Prerequisites

Install

Quickstart

Available Tools

Memory tools (always on)

Agent admin tools (opt-in)

Configuration

Running over HTTP / SSE

Programmatic Embedding

Sharing Memory Across Clients

Troubleshooting

Next Steps