A Filesystem MCP for Agent Memory

MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others.

The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.

How it fits together

 ┌──────────────┐     MCP/stdio     ┌────────────────────┐     filesystem      ┌────────────────────────┐
 │ Kiro / Claude│ ◄───────────────► │ mcp-server-memory  │ ◄─────────────────► │ agent-memory-daemon    │
 │   / Cursor   │                   │  (this package)    │   ~/.agent-memory/   │  (runs in background)  │
 └──────────────┘                   └────────────────────┘                     └────────────────────────┘

• The MCP server reads/writes files under ~/.agent-memory/
• The daemon watches the same directory and runs consolidation + extraction passes
• They never talk to each other directly — the filesystem is the contract

Tools exposed

memory_read

Read the agent memory index (MEMORY.md) and optionally specific topic files. Call with no arguments to load only the lightweight index (cheap). Pass topics only when you need the full content of a specific topic file.

memory_append_session

Append a session summary to the sessions directory. The daemon will later extract durable memories from it. Call this at the end of meaningful exchanges. Keep summaries focused on durable findings and decisions (target 300–800 tokens), not play-by-play — longer summaries cost more during consolidation.

memory_search

Search memory files for a substring. Use this to recall specific facts without loading everything.

Install

npm install -g mcp-agent-memory

Quick start (interactive wizard)

The fastest way to set everything up — memory directory, daemon, client configs, logs, and LaunchAgent — is the setup wizard:

mcp-agent-memory --setup

It asks six questions:

1. Memory directory — where .agent-memory/ lives (default ~/.agent-memory)
2. Install the consolidation daemon? — say "no" for MCP-only mode (agents can read/write/search memory, but no automatic consolidation)
3. LLM backend — bedrock, openai, or kiro (skipped if you declined the daemon)
4. Consolidation settings — min_hours, min_sessions, extraction interval, max chars
5. Run mode — standalone (start manually) or launchagent (auto-start at login, macOS only)
6. Logs directory + TTL — where to put logs, and how many days to keep them (0 = forever)
7. Client registration — auto-register the MCP server in Kiro, Claude Desktop, and/or Cursor configs (existing MCP entries are preserved)

When you select the kiro backend, the wizard also copies a lean agent to ~/.kiro/agents/memconsolidate.json that cuts token usage by ~7× (see Kiro backend).

When you select launchagent, the wizard checks that agent-memory-daemon is installed (and offers to npm install -g it if not), then registers and starts the plist.

CLI reference

mcp-agent-memory                       # run as an MCP server (normal mode — clients spawn it)
mcp-agent-memory --setup               # first-time interactive setup
mcp-agent-memory --configure           # re-run most steps; can add/remove the daemon later
mcp-agent-memory --remove              # interactive uninstall (backup memory, clean configs)

# macOS LaunchAgent control:
mcp-agent-memory --daemon status       # is the daemon running?
mcp-agent-memory --daemon start        # load and start
mcp-agent-memory --daemon stop         # unload (keeps the plist)
mcp-agent-memory --daemon restart      # stop + start
mcp-agent-memory --daemon remove       # unload and delete the plist

--remove preserves other entries in client MCP configs — only the memory key is deleted. By default it backs up ~/.agent-memory/ to a timestamped .bak-* directory so you can restore your consolidated memories.

Manual install

If you'd rather skip the wizard, here's how to do it by hand.

Install the daemon (optional)

The MCP server works standalone — it just reads and writes files under ~/.agent-memory/. Memories persist, but they won't be consolidated or extracted from sessions until you add the daemon.

npm install -g agent-memory-daemon

# copy the example config
mkdir -p ~/.agent-memory
cp examples/memconsolidate.toml ~/.agent-memory/memconsolidate.toml

# start the daemon
agent-memory-daemon start ~/.agent-memory/memconsolidate.toml

See examples/memconsolidate.toml for a ready-to-use config that matches the directory layout this MCP server expects.

Run the daemon at login (macOS)

Instead of starting the daemon manually, register it as a LaunchAgent:

./scripts/daemon.sh start          # install plist, load it, start at login
./scripts/daemon.sh status         # check if it's running
./scripts/daemon.sh stop           # unload (keeps the plist)
./scripts/daemon.sh remove         # unload and delete the plist

Pass a custom config path as a second arg: ./scripts/daemon.sh start /path/to/config.toml. Logs land in ~/.agent-memory/logs/daemon.{out,err}.log. remove leaves your config and memory files untouched.

Use Kiro as the LLM backend

If you have Kiro credits, you can run the daemon through kiro-cli instead of paying for Bedrock or OpenAI API calls. This requires agent-memory-daemon ≥ 2.7 (branch feat/kiro-backend) which adds a kiro backend.

[llm_backend]
name = "kiro"
# optional overrides:
# binary = "/custom/path/to/kiro-cli"
# agent = "memconsolidate"          # set to "" to use Kiro's default session context (not recommended)
# model = "claude-sonnet-4-20250514"
# timeoutMs = 300000

Use a lean agent to cut token usage by ~7×. By default, every kiro-cli chat call loads Kiro's full system prompt plus every MCP tool schema from your global config — roughly 12–18K extra input tokens per call. Create a minimal agent that skips all of that:

cp examples/kiro-agent-memconsolidate.json ~/.kiro/agents/memconsolidate.json

The Kiro backend passes --agent memconsolidate automatically, so no further config is needed. Measured on a trivial prompt: 0.01 credits with the lean agent vs. 0.07 credits with the default (same output quality).

See examples/kiro-agent-memconsolidate.json — the agent has mcpServers: {}, tools: [], and useLegacyMcpJson: false so it doesn't inherit anything from your global Kiro config.

Configure clients manually

The --setup and --configure wizards handle this for you. This section is for users who want to wire things up by hand.

Kiro (CLI and IDE)

Edit ~/.kiro/settings/mcp.json:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "mcp-agent-memory"],
      "env": {
        "MEMORY_DIRECTORY": "~/.agent-memory/memory",
        "SESSION_DIRECTORY": "~/.agent-memory/sessions"
      },
      "disabled": false,
      "timeout": 30000,
      "autoApprove": ["memory_read", "memory_search", "memory_append_session", "memory_daemon_status"]
    }
  }
}

Why autoApprove? All memory tools are local-only filesystem operations — they read/write markdown files under ~/.agent-memory/ and never make network calls. Adding them to autoApprove lets Kiro call them without prompting you for confirmation each time, which is essential for the seamless "read memory at session start" experience.

Then ask Kiro: "Read my memory index." or "Remember this: I prefer pnpm over npm."

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "mcp-agent-memory"],
      "env": {
        "MEMORY_DIRECTORY": "~/.agent-memory/memory",
        "SESSION_DIRECTORY": "~/.agent-memory/sessions"
      },
      "autoApprove": ["memory_read", "memory_search", "memory_append_session", "memory_daemon_status"]
    }
  }
}

Restart Claude Desktop. The memory_* tools will appear.

Cursor

Add to ~/.cursor/mcp.json with the same server block (including autoApprove).

Environment variables

Both paths must match what your agent-memory-daemon config uses.

Recommended agent prompt

Tell your agent to call memory_read at the start of a conversation and memory_append_session at the end. Example steering rule for Kiro (~/.kiro/steering/memory.md):

At the start of every session, call memory_read (no arguments) to load my memory
index. Only pass `topics` when the task genuinely needs the full content of a
specific topic file.

When you learn something durable about me, my projects, or my preferences, call
memory_append_session with a concise markdown summary. Target 300-800 tokens,
use structured headers and bullets (not prose), and focus on durable findings
and decisions — not play-by-play. Verbose summaries cost more during the
daemon's consolidation pass.

Token usage tips

Each of the three tools has a different cost profile. A few practices keep inference + consolidation bills low:

• memory_read with no arguments returns only the MEMORY.md index (typically <1 KB). Prefer this over topics unless you need full content.
• memory_search is substring-based and returns ≤3 matching lines per file — cheaper than loading whole topic files.
• memory_append_session costs nothing at call time, but every session gets processed by the daemon's LLM during consolidation. Keep summaries concise and structured.
• Consolidate or prune old topic files occasionally. Run mcp-agent-memory --configure — it now warns if your memory directory exceeds 25 files or 200 KB.
• Session pruning after extraction is handled by the daemon, not the MCP server. See agent-memory-daemon's config for options that archive or delete sessions after they're processed (prevents the daemon from re-scanning old sessions forever).

License

MIT