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  3. MCP Agent Memory
MCP Agent Memory logo
Health: ActiveRecent health check succeeded.Last checked 9/6/2026, 11:33:00 PM

MCP Agent Memory

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View Repository4 GitHub StarsTotal stargazers on GitHub for the source repository (4 stars).Visit Website
memoryfilesystemmcpagent-context

Filesystem-based MCP server for reading, appending, and searching persistent agent memory.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Automated check passedβ€” started and listed 4 tools correctly (1mo ago).
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "tverney-mcp-agent-memory": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-agent-memory"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (4) Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

This server exposes a filesystem bridge for agent memory through MCP. It stores memory under ~/.agent-memory/, while the optional agent-memory-daemon performs consolidation and extraction. Use it with MCP clients that need persistent session context and searchable memory.

Use cases

β€’Read the memory index and selected topic files
β€’Append focused session summaries for later extraction
β€’Search stored memory for specific facts
β€’Connect persistent memory to Claude Desktop or Cursor

Key features

β€’Reads MEMORY.md and selected topic files
β€’Appends summaries to the sessions directory
β€’Searches memory files by substring
β€’Uses the filesystem as the server-daemon contract
β€’Supports optional consolidation and extraction through agent-memory-daemon

Capabilities & Tool Schemas (4) ~382 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Verified live Verified liveCaptured by calling this server’s live tools/list endpoint.

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Agent Memory.

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 β€” longer summaries cost more during consolidation.

memory_search

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

memory_daemon_status

Check whether the memory consolidation daemon is running. Reports if the daemon is not installed or not available on this platform.

Documentation Overview

A Filesystem MCP for Agent Memory

mcp-agent-memory MCP server

MCP server that exposes agent-memory-daemon to any MCP-compatible client β€” 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.

output

How it fits together

Code
 β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”     MCP/stdio     β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”     filesystem      β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
 β”‚ Kiro / Claudeβ”‚ ◄───────────────► β”‚ mcp-server-memory  β”‚ ◄─────────────────► β”‚ agent-memory-daemon    β”‚
 β”‚   / Cursor   β”‚                   β”‚  (this package)    β”‚   ~/.agent-memory/   β”‚  (runs in background)  β”‚
 β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜                   β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜                     β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
  • 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 β€” 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.

ParameterTypeRequiredDescription
topicsstring[]NoTopic file names to load in full (e.g., ["preferences", "projects"]). Omit to return the index only.

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 β€” longer summaries cost more during consolidation.

ParameterTypeRequiredDescription
contentstringYesMarkdown-formatted session summary. Use structured headers and bullets for better extraction; avoid verbose prose.
sourcestringNoOrigin tag, e.g., "kiro", "claude-desktop"

memory_search

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

ParameterTypeRequiredDescription
querystringYesThe substring to search for across all memory files.

Install

Terminal
npm install -g mcp-agent-memory

Quick start (interactive wizard)

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

bash
mcp-agent-memory --setup

It asks six questions:

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

bash
mcp-agent-memory                       # run as an MCP server (normal mode β€” 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 β€” 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 β€” 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.

Terminal
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:

bash
./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 β‰₯ 2.7 (branch feat/kiro-backend) which adds a kiro backend.

toml
[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 ~7Γ—. By default, every kiro-cli chat call loads Kiro's full system prompt plus every MCP tool schema from your global config β€” roughly 12–18K extra input tokens per call. Create a minimal agent that skips all of that:

bash
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 β€” 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:

config.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 β€” 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):

config.json
{
  "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

VariableDefaultDescription
MEMORY_DIRECTORY~/.agent-memory/memoryWhere the daemon stores consolidated memory files
SESSION_DIRECTORY~/.agent-memory/sessionsWhere agent-written session summaries land

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

Recommended agent prompt

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
4
Stargazers on the source repository.
npm downloads
109
Package downloads in the last 30 days.
Last commit
29d ago
Most recent push to the default branch.
Availability
100%
Our rolling endpoint + install checks that succeeded.
Install check
Passed
Our sandbox started it and listed its tools.
Tools exposed
4
Callable tools this server registers over MCP.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about MCP Agent Memory

It provides tools to read memory, append session summaries, and search memory files for substrings.

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Technical Specs & Signals

Category🧠Knowledge & Memory
PricingFree
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
AuthNo auth required
ClientsClaude Desktop, Cursor
Last updatedAug 12, 2026
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars4
GitHub Star CountTotal stargazers on GitHub representing community popularity (4 stars).
Last commit29d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 12, 2026
npm downloads109/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
72Quality signal: Great Β· 72/100How this signal is calculated β–Ύ
Server availability25/25
Verified ownership10/20
Documentation & tools30/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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Scanned 25d ago via OSV.dev Β· mcp-agent-memory (npm)

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