Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
A fully local MCP server for long-term memory with semantic search
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"longterm-memory": {
"command": "npx",
"args": [
"-y",
"longterm-memory-mcp"
]
}
}
}Run this in your terminal
claude mcp add longterm-memory -- npx -y longterm-memory-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"longterm-memory": {
"command": "npx",
"args": [
"-y",
"longterm-memory-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"longterm-memory": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"longterm-memory-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account MarcelRoozekrans, which owns the repo
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This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.6.1) reached the registry 6 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Context7, Codebase Memory, Exa
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Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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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:
| Feature | mcp-mem0 | This project |
|---|---|---|
| Storage | PostgreSQL / Supabase | SQLite (Node's built-in node:sqlite) |
| Embeddings | OpenAI API | Local transformer (all-MiniLM-L6-v2) |
| Vector search | Cloud vector DB | In-process cosine similarity |
| LLM dependency | OpenAI / OpenRouter / Ollama | None |
| Setup | Database + API keys | `npx longterm-memory-mcp` |
| Tool | Description |
|---|---|
save_memory | Store text with auto-generated semantic embedding, tags, importance, and type |
search_memory | Find relevant memories using natural language queries (cosine similarity) |
update_memory | Modify an existing memory's content, metadata, tags, importance, or type |
delete_memory | Remove a specific memory by ID |
delete_all_memories | Wipe all memories (irreversible) |
get_all_memories | List all stored memories (paginated) |
memory_stats | Get count and database location |
| Tool | Description |
|---|---|
search_by_type | Filter memories by category (general, fact, preference, conversation, task, ephemeral) |
search_by_tags | Find memories matching any of the provided tags |
search_by_date_range | Find memories created within a specific date range (ISO format) |
| Tool | Description |
|---|---|
create_backup | Manually trigger a database backup with JSON export |
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:
long-term-memory skill (Claude learns to recall context at session start, save insights after tasks, and deduplicate memories)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 longterm-memory-mcp@1.6.0, or use @latest, which checks the registry on every start.
npm install -g longterm-memory-mcp
longterm-memory-mcp
git clone https://github.com/MarcelRoozekrans/LongtermMemory-MCP.git
cd LongtermMemory-MCP npm install && npm run build npm start
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"] } } }
Add to claude_desktop_config.json:
{
"mcpServers": { "longterm-memory": { "command": "npx", "args": ["-y", "longterm-memory-mcp"] } } }
The repo includes agent instructions that teach AI agents how to use memory effectively (automatic recall, save patterns, deduplication):
| File | Purpose |
|---|---|
skills/long-term-memory/SKILL.md | Self-contained skill — auto-loaded by Claude Code plugin, can be referenced from any MCP client |
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- .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.
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" } } } }
Each memory has a memory_type that determines how it's categorized and how quickly it decays:
| Type | Description | Decay half-life |
|---|---|---|
general | Default catch-all | 60 days |
fact | Verified information | 120 days |
preference | User/project preferences | 90 days |
conversation | Conversation context | 45 days |
task | Task-related notes | 30 days |
ephemeral | Short-lived context | 10 days |
["auth", "backend"]). Search with search_by_tags.core, identity, or pinned skip decay entirely.Memories decay over time to keep the store relevant:
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.
Memories end up in the database and in its JSON backups, so content is filtered before it is stored:
… is never stored, embedded or hashed. An unclosed removes everything after it. Content that is empty once the spans are removed is 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.| Pattern | Matches |
|---|---|
private-key | PEM / OpenSSH / PGP private key headers (certificates are allowed) |
github-token | ghp_, gho_, ghu_, ghs_, ghr_ and github_pat_ tokens |
api-key | sk-… style API keys |
aws-access-key | AKIA… / ASIA… access key ids |
jwt | JSON Web Tokens |
slack-token | xoxb-, xoxp- and similar Slack tokens |
secret-assignment | random-looking values after password=, token:, secret=, api_key=, KEY= and similar. References ($VAR, ${{ … }}), placeholders (<…>), calls and plain words are allowed |
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. 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.
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):
recall-sessions/ next to the database. Later prompts in that session cost one node start, about 30 ms, and no search.npx longterm-memory-mcp@ 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.
| Variable | Default | Meaning |
|---|---|---|
MEMORY_RECALL_ENABLED | true | false turns the hook off |
MEMORY_RECALL_K | 5 | at most this many memories (1–50) |
MEMORY_RECALL_THRESHOLD | 0.5 | minimum cosine similarity (-1 to 1) |
MEMORY_RECALL_MAX_TOKENS | 400 | cap on the injected block, estimated at 4 characters per token |
MEMORY_RECALL_STATE_DIR | /recall-sessions | where the once-per-session markers live; markers older than 30 days are removed |
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 are managed automatically and can also be triggered manually via the create_backup tool.
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