Longterm Memory

[LongtermMemory-MCP]

LongtermMemory-MCP

[codecov] [GitHub Sponsors]

A fully local MCP server that gives AI agents persistent, semantic long-term memory — without any cloud dependencies.

Inspired by mcp-mem0, but runs 100% on your machine:

Tools

Core

Search

Maintenance

Quick Start

Claude Code Plugin (recommended)

Install via the Claude Code marketplace — this sets up both the MCP server and a companion skill that teaches Claude how to use memory effectively:

/plugin marketplace add MarcelRoozekrans/LongtermMemory-MCP/plugin install longterm-memory@longterm-memory-marketplace

This automatically:

• Configures the MCP server (no manual JSON editing), pinned to the plugin's version: a plugin update also updates the server
• Adds the automatic recall hook
• Installs the long-term-memory skill (Claude learns to recall context at session start, save insights after tasks, and deduplicate memories)

Use with npx (no install needed)

npx longterm-memory-mcp

npx keeps running the version it cached first and does not look for updates. To move to a new release, name the version, as in npx -y [email protected], or use @latest, which checks the registry on every start.

Or install globally

npm install -g longterm-memory-mcplongterm-memory-mcp

Or from source

git clone https://github.com/MarcelRoozekrans/LongtermMemory-MCP.gitcd LongtermMemory-MCPnpm install && npm run buildnpm start

Configuration

Claude Code

If you installed via the plugin marketplace, the MCP server is already configured. For manual setup, add to your MCP settings (~/.claude/settings.json or project .claude/settings.json):

{  "mcpServers": {    "longterm-memory": {      "command": "npx",      "args": ["-y", "longterm-memory-mcp"]    }  }}

Claude Desktop

Add to claude_desktop_config.json:

{  "mcpServers": {    "longterm-memory": {      "command": "npx",      "args": ["-y", "longterm-memory-mcp"]    }  }}

Agent Instructions

The repo includes agent instructions that teach AI agents how to use memory effectively (automatic recall, save patterns, deduplication):

Database Location

By default, memories are stored in a shared, user-scoped location:

~/.longterm-memory-mcp/memories.db

This means every project and every MCP client shares the same memory pool — you save a memory in one project and it's available everywhere.

Several sessions can use the same database at once. Each server process reads and writes the shared file directly (SQLite in WAL mode), so a memory saved in one session is visible to every other session right away, and no session overwrites what another saved. Requires Node.js 22.13 or later.

Databases from older releases open unchanged. A database from v1.0–1.3, which has no schema_meta table, is migrated in place with all its memories kept; a copy named memories.db.pre-migration-<timestamp>.bak is written next to it first.

Upgrading from 1.4 or earlier: stop every running session that uses the old version before starting one with the new version. Older releases keep the whole database in memory and rewrite the file on each save, so an old process left running would overwrite what new sessions saved.

Per-project database

To isolate memories for a specific project, set the MEMORY_DB_PATH environment variable:

{  "mcpServers": {    "longterm-memory": {      "command": "npx",      "args": ["-y", "longterm-memory-mcp"],      "env": {        "MEMORY_DB_PATH": "/path/to/project/memories.db"      }    }  }}

Memory Types

Each memory has a memory_type that determines how it's categorized and how quickly it decays:

Tags & Importance

• Tags: Categorize memories with string tags (e.g. ["auth", "backend"]). Search with search_by_tags.
• Importance (1–10): Controls how resistant a memory is to decay. Default is 5. Higher importance decays more slowly.
• Protected tags: Memories tagged with core, identity, or pinned skip decay entirely.

Decay & Reinforcement

Memories decay over time to keep the store relevant:

• Decay: Each memory type has a half-life (see table above). Importance decreases exponentially based on time since last access, with a floor that prevents full deletion.
• Reinforcement: Every time a memory is accessed via search, its importance increases by +0.1 (up to a max of 10). Frequently accessed memories stay important.
• Lazy evaluation: Decay is calculated on access, not on a timer — no background processes needed.

Content Deduplication

Memory content is hashed (SHA-256) on save. If identical content already exists, the save is rejected with a reference to the existing memory ID. This prevents duplicate entries automatically.

Content Guard

Memories end up in the database and in its JSON backups, so content is filtered before it is stored:

• <private> spans are removed. Text inside <private>…</private> is never stored, embedded or hashed. An unclosed <private> removes everything after it. Content that is empty once the spans are removed is rejected.
• Secrets are rejected. save_memory and update_memory refuse content, metadata values and tags that look like a secret. The error names the pattern that matched and never the value.

Configure it with environment variables:

{  "mcpServers": {    "longterm-memory": {      "command": "npx",      "args": ["longterm-memory-mcp"],      "env": {        "MEMORY_GUARD_DISABLE": "jwt,slack-token",        "MEMORY_GUARD_EXTRA_PATTERNS": "{\"internal-host\": \"\\\\b[a-z0-9-]+\\\\.corp\\\\.example\\\\b\"}"      }    }  }}

• MEMORY_GUARD_DISABLE: a comma-separated list of pattern names to turn off, or all for every built-in pattern. <private> spans are removed either way. An unknown name stops the server at startup.
• MEMORY_GUARD_EXTRA_PATTERNS: a JSON object of extra patterns to reject, as name → regular expression.

The guard applies to new saves and updates only. Memories stored before it existed are not rescanned.

Automatic Recall

The Claude Code plugin ships a UserPromptSubmit hook that recalls memories without the agent having to ask. On the first prompt of each session it searches with the prompt text and adds the best matches to the context as a short list:

Long-term memories that may be relevant (longterm-memory; search_memory gives the full text):- [2026-10-22 fact] pkill -f <pattern> also matches the agent's own shell … (id 31ece450-…)

• Once per session: the hook keeps a marker file per session id in recall-sessions/ next to the database. Later prompts in that session cost one node start, about 30 ms, and no search.
• Project: the hook takes the project name from the session's working directory. A memory that names the project in its content, tags or metadata ranks a little higher. The name is not part of the search text: a short prompt would then match on the project name alone.
• Cheap when it misses: nothing is injected when no memory reaches the threshold, and the block never exceeds the token cap.
• Content guard: a stored memory that the guard rejects, such as one saved before the guard existed, is never injected.
• Never blocks a prompt: errors go to stderr and the prompt continues.
• Pinned version: the hook runs npx longterm-memory-mcp@<plugin version> recall --hook, so a cached older copy is never used. The plugin's MCP server is pinned the same way.

Configure it with environment variables in your Claude Code settings (env in ~/.claude/settings.json). The hook runs in Claude Code's environment, not the MCP server's, so a custom MEMORY_DB_PATH has to be set there too.

Recall CLI

The hook calls the recall subcommand, which also works on its own:

npx longterm-memory-mcp recall "how do we deploy the stack"npx longterm-memory-mcp recall --k 3 --threshold 0.4 --project docker "deploy"

It prints the same list the hook injects, or No relevant memories found. on stderr. Options: --k, --threshold, --max-tokens and --project (default: the current directory's name, "" for none). It does not create a database that does not exist yet. With --hook it reads a Claude Code UserPromptSubmit event from stdin and answers with additionalContext.

Backups

Backups are managed automatically and can also be triggered manually via the create_backup tool.

• Auto-backup: Triggers every 24 hours or when the memory count reaches a multiple of 100.
• Retention: The last 10 backups are kept; older ones are pruned automatically.
• Format: Each backup is a timestamped directory containing a consistent snapshot of the SQLite database and a JSON export of all memories.
• Location: ~/.longterm-memory-mcp/backups/ by default, or set MEMORY_BACKUP_PATH:

{  "mcpServers": {    "longterm-memory": {      "command": "npx",      "args": ["-y", "longterm-memory-mcp"],      "env": {        "MEMORY_BACKUP_PATH": "/path/to/backups"      }    }  }}

How It Works

1. Save: Text is embedded locally using all-MiniLM-L6-v2 (384-dim vectors) and stored in SQLite alongside the raw content, metadata, tags, importance, and type. Content is deduplicated via SHA-256 hash.
2. Search: Your query is embedded with the same model, then compared against every stored memory using cosine similarity. Results above the threshold are returned ranked by relevance. Accessed memories are reinforced automatically.
3. Decay: Over time, unused memories lose importance based on their type's half-life. Protected and frequently accessed memories resist decay.
4. Persist: Every change is written straight to the SQLite database on disk, so concurrent sessions share one consistent store. No background processes, no servers to maintain.

The embedding model (~30MB quantized) is downloaded once on first use and cached locally.

Architecture

src/                           — MCP server source  index.ts                     — Entry point (stdio server, or the `recall` subcommand)  paths.ts                     — Database and recall-state path resolution  cli.ts                       — `recall` subcommand, standalone and hook mode  recall.ts                    — Recall search, project ranking, guard filter, token-capped list  recall-session.ts            — Once-per-session markers for the recall hook  server.ts                    — MCP server factory + 11 tool definitions  memory-store.ts              — SQLite storage + vector search + decay integration  embeddings.ts                — Local embedding engine (Xenova/transformers)  decay.ts                     — DecayEngine (lazy decay, reinforcement, protected tags)  backup.ts                    — BackupManager (auto-backup, JSON export, pruning)  content-guard.ts             — Strips <private> spans, rejects secrets  types.ts                     — TypeScript interfaces (Memory, Embedder, config types)
hooks/                         — Claude Code plugin hooks  hooks.json                   — UserPromptSubmit → recall gate  recall-gate.mjs              — Dependency-free gate: runs the recall CLI once per session
skills/                        — Claude Code plugin skill  long-term-memory/SKILL.md    — Self-contained agent instructions + skill
.claude-plugin/                — Plugin & marketplace metadata  plugin.json                  — Plugin manifest  marketplace.json             — Marketplace manifestscripts/                       — Plugin launch helpers (plain Node, no dependencies)  launch-server.mjs            — Starts the MCP server pinned to the plugin version  plugin-package.mjs           — longterm-memory-mcp@<plugin version>.mcp.json                      — MCP server for working on this repo.vscode/mcp.json               — VS Code MCP server config

Benchmarks

Run with npm run bench. Results from an in-memory store using mock embeddings (isolates store/SQLite performance from model latency):

Cosine Similarity

Memory Store Operations

Search (semantic, at scale)

Decay Engine

Development

npm install          # Install dependenciesnpm run build        # Compile TypeScriptnpm test             # Run all testsnpm run bench        # Run benchmarksnpm run test:watch   # Watch modenpm run test:coverage # Coverage report

Contributing

This project uses Conventional Commits and semantic-release for automated versioning.

Commit message format

<type>(<optional scope>): <description>
[optional body]
[optional footer(s)]

Breaking changes: Add ! after the type (e.g., feat!: remove deprecated API) or include a BREAKING CHANGE: footer. This triggers a major version bump.

Examples

git commit -m "feat: add memory tagging support"git commit -m "fix: handle empty search query gracefully"git commit -m "feat!: change default database location"git commit -m "docs: update configuration examples"

Commit messages are validated locally via commitlint + husky git hooks. Non-conforming messages will be rejected.

Releases

Releases are fully automated. When commits are pushed to main:

1. semantic-release analyzes commit messages
2. Determines the next version (major / minor / patch)
3. Generates release notes from commits
4. Updates CHANGELOG.md
5. Publishes to npm
6. Creates a GitHub Release

No manual version bumps or tags needed.

Dependency Updates

Dependencies are managed automatically by Renovate. Patch and minor devDependency updates are auto-merged after CI passes. Major updates create PRs for manual review.

License

MIT