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Memory MCP Server

by j0hanzversion 1.7.0i★ –iRuns on your computer
Registry nameio.github.j0hanz/memory-mcp

Install

Overview

Description from the maker (original English)

SQLite-backed MCP server for persistent memory, full-text retrieval, and graph traversal.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "@j0hanz/memory-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add memory -- npx -y @j0hanz/memory-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "@j0hanz/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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "memory": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@j0hanz/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.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account j0hanz, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7264 servers in this category
  • Published to the registry more recently than 4% of the other 7264 servers in this category
  • Basic checks equal to or better than 100% of the other 7264 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Memory MCP Server safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.7.0) reached the registry 8 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Memory MCP

A SQLite-backed MCP server for persistent memory storage, full-text retrieval, and relationship graph traversal.

Overview

Memory MCP provides a local, persistent memory layer for MCP-enabled assistants. It stores SHA-256-addressed memory items in SQLite with FTS5-powered full-text search, a directed relationship graph, BFS recall traversal, and token-budget-aware context retrieval — all accessible over stdio transport with no external dependencies.

Key Features

  • 13 MCP tools for CRUD, batch operations, FTS5 search, BFS graph recall, token-budget context retrieval, relationships, and stats.
  • Full-text search over content and tags via SQLite FTS5 with importance and type filters.
  • Graph recall with BFS traversal, bounded frontier, and MCP progress notifications per hop.
  • Token-budget retrieval (retrieve_context) selects memories that fit a caller-specified token budget — no manual pagination needed.
  • Strict Zod input validation with typed output envelopes and SHA-256 hash addressing.
  • Resource support with internal://instructions (Markdown guide) and memory://memories/{hash} URI template with hash auto-completion.
  • stdio transport with clean shutdown handling (SIGINT, SIGTERM) and no HTTP endpoints. |

Requirements

  • Node.js >=24.
  • SQLite with FTS5 support (verified at startup).
  • Any MCP client that supports stdio command servers.

Quick Start

Use the npm package directly with npx — no installation required:

{

"mcpServers": { "memory-mcp": { "command": "npx", "args": ["-y", "@j0hanz/memory-mcp@latest"] } } }

[!TIP]

The server uses stdio transport only; no HTTP endpoint is exposed. Stdout must not be polluted by custom logging.

Or run with Docker:

docker run --rm -i ghcr.io/j0hanz/memory-mcp:latest

Client Configuration

Install in VS Code

Workspace file .vscode/mcp.json:

{

"servers": { "memory-mcp": { "command": "npx", "args": ["-y", "@j0hanz/memory-mcp@latest"] } } }

CLI:

code --add-mcp '{"name":"memory-mcp","command":"npx","args":["-y","@j0hanz/memory-mcp@latest"]}'

Install in VS Code Insiders

CLI:

code-insiders --add-mcp '{"name":"memory-mcp","command":"npx","args":["-y","@j0hanz/memory-mcp@latest"]}'

Install in Cursor

~/.cursor/mcp.json:

{

"mcpServers": { "memory-mcp": { "command": "npx", "args": ["-y", "@j0hanz/memory-mcp@latest"] } } }

Install in Claude Desktop / Claude Code

claude_desktop_config.json:

{

"mcpServers": { "memory-mcp": { "command": "npx", "args": ["-y", "@j0hanz/memory-mcp@latest"] } } }

CLI:

claude mcp add memory-mcp -- npx -y @j0hanz/memory-mcp@latest

Install in Windsurf

MCP config:

{

"mcpServers": { "memory-mcp": { "command": "npx", "args": ["-y", "@j0hanz/memory-mcp@latest"] } } }

Run with Docker

# Pull and run (stdio mode)

docker run --rm -i \ -e MEMORY_DB_PATH=/data/memory.db \ -v memory-data:/data \ ghcr.io/j0hanz/memory-mcp:latest

MCP client config:

{

"mcpServers": { "memory-mcp": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "MEMORY_DB_PATH=/data/memory.db", "-v", "memory-data:/data", "ghcr.io/j0hanz/memory-mcp:latest" ] } } }

Documentation Maintenance

  • Owner: maintainers updating MCP behavior in src/ must update README.md and affected mcp/ mirror pages in the same PR.
  • Link/version policy: use pinned https://modelcontextprotocol.io/specification/2025-11-25/... links for protocol references; avoid latest and mixed legacy targets.
  • Drift-check checklist:
  • Re-verify capability declarations in src/server.ts.
  • Reconcile tool/resource/prompt docs with src/tools/index.ts, src/resources/index.ts, and src/prompts/index.ts.
  • Confirm limitations/gotchas in src/instructions.md match runtime behavior.
  • Validation commands: npm run type-check, npm run test:fast, npm run build.

MCP Surface

Tools Summary
ToolCategoryNotes
store_memoryWriteIdempotent by content+sorted tags hash
store_memoriesWriteBatch (1–50), transaction-wrapped
get_memoryReadHash lookup
update_memoryWriteReturns old_hash + new_hash
delete_memoryWriteCascades relationship deletion
delete_memoriesWriteBatch (1–50), transaction-wrapped
search_memoriesReadFTS5 + importance/type filters + cursor
create_relationshipWriteIdempotent directed edge creation
delete_relationshipWriteDeletes exact directed edge
get_relationshipsReadDirection filter + linked memory fields
recallReadFTS5 seed + BFS traversal (depth 0–3)
retrieve_contextReadToken-budget-aware context retrieval
memory_statsReadStore aggregates and type breakdown

store_memory

Store a new memory with content, tags, and optional type/importance. Idempotent — storing the same content+tags returns the existing hash with created: false.

NameTypeRequiredDefaultDescription
contentstringYes—Memory content (1–100000 chars)
tagsstring[]Yes—1–100 tags, each max 50 chars, no whitespace
memory_typeenumNogeneralgeneral, fact, plan, decision, reflection, lesson, error, gradient
importanceintegerNo0Priority 0–10

Returns: { hash, created }


store_memories

Store multiple memories in one transaction (max 50 items).

NameTypeRequiredDescription
itemsArray Yes1–50 items, each with content, tags, optional memory_type, optional importance

Returns: { items, succeeded, failed }


get_memory

Retrieve one memory by its SHA-256 hash.

NameTypeRequiredDescription
hashstringYes64-char lowercase SHA-256 hex

Returns: Memory or { ok: false, error } on E_NOT_FOUND.


update_memory

Update content and optionally tags for an existing memory. Returns both hashes.

NameTypeRequiredDefaultDescription
hashstringYes—Existing memory hash
contentstringYes—Replacement content
tagsstring[]NoExisting tagsReplacement tags

Returns: { old_hash, new_hash }


delete_memory

Delete one memory by hash. Cascades to related relationship rows.

NameTypeRequiredDescription
hashstringYesMemory hash

Returns: { hash, deleted }


delete_memories

Delete multiple memories by hash in one transaction.

NameTypeRequiredDescription
hashesstring[]Yes1–50 memory hashes

Returns: { items, succeeded, failed }


search_memories

Full-text search over memory content and tags using FTS5. Supports importance and type filters with cursor pagination.

NameTypeRequiredDefaultDescription
querystringYes—Search text (1–1000 chars)
limitintegerNo20Results per page (1–100)
cursorstringNo—Pagination cursor from previous response

| min_importance | integer | No | — | Only return memories

Only the beginning is shown; read the rest in the repo

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