Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Memory Lean

by zamansheikhversion 1.5.0i★ –iRuns on your computer
Registry nameio.github.zamansheikh/memory-lean

Install

Overview

Description from the maker (original English)

Token-lean memory for AI agents: a knowledge graph searched cheaply. Drop-in for server-memory.

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).
  • You fill in yourself: MEMORY_FILE_PATH

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-lean": {
      "command": "npx",
      "args": [
        "-y",
        "memory-lean"
      ],
      "env": {
        "MEMORY_FILE_PATH": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add memory-lean --env MEMORY_FILE_PATH=your-value -- npx -y memory-lean

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "memory-lean": {
      "command": "npx",
      "args": [
        "-y",
        "memory-lean"
      ],
      "env": {
        "MEMORY_FILE_PATH": "your-value"
      }
    }
  }
}

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-lean": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "memory-lean"
      ],
      "env": {
        "MEMORY_FILE_PATH": "your-value"
      }
    }
  }
}

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.

Values you fill in

  • MEMORY_FILE_PATH env
    Where the graph file lives (default ~/.claude/memory-graph/memory.jsonl)

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 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account zamansheikh, 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 7246 servers in this category
  • Published to the registry more recently than 64% of the other 7246 servers in this category
  • Basic checks equal to or better than 100% of the other 7246 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 Lean 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 (1.5.0) reached the registry 21 days 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 today
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 20 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-lean

Long-term memory for AI coding agents that doesn't burn the context window.

A knowledge graph your agent searches cheaply, and a web UI where you can see and edit all of it.

Quick start · Web UI · How it works · Tools · Setup for 12 agents · Contributing

memory-lean is an MCP server that gives Claude Code, Codex, Cursor, MiMo Code and any other MCP client a memory that lasts between sessions: which projects exist, what depends on what, which version shipped, what is still pending, and which rules were learned the hard way. It is a drop-in replacement for the reference memory server (@modelcontextprotocol/server-memory), with the same file and tool names, but its answers are about 40 times smaller.

Highlights

About 40× smaller answers. Search returns a ranked list of names and the lines that matched, not every entity in full, so the agent can afford to check its memory before every task.

A web UI for people. See the whole graph grouped by type, follow relations, and add, edit or delete anything. Agent writes show up live.

Drop-in replacement. Same memory.jsonl file and the same nine tools as the reference server. Switch in, and switch back whenever you like.

Works with every agent. Copy-paste setup for Claude Code, MiMo Code, Codex, Cursor, Copilot, Gemini CLI, Zed, JetBrains and more, plus the instructions that teach the agent to use it.

Stays small by itself. Short facts, a cap per entity, and an archive for the overflow, so the graph never grows into a wall of text.

Private and safe. Plain local files, daily backups, a write lock for parallel sessions, and no network access. One server file, zero dependencies.

The numbers

Measured on a real graph of 237 entities, 355 relations and 1,160 facts (tokens ≈ characters ÷ 4):

CallReference servermemory-lean
read_graph~77,800 tokens~2,000 tokens40× smaller
search_nodes, average of 5 common words~31,000 tokens~770 tokens40× smaller

A narrow search that matches one or two entities saves less, because there is little to trim. To measure your own graph, run node tools/bench.mjs from a clone; it is read-only and prints sizes, never content.

Quick start

Claude Code: install the plugin. It adds the server, the instructions as a skill, a short reminder at the start of each session, and /memory-ui.

/plugin marketplace add zamansheikh/memory-lean

/plugin install memory-lean@memory-lean

Any other agent: add the server to its MCP config, then give it the instructions.

{

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

npx -y memory-lean --protocol >> AGENTS.md   # into the rules file your agent reads

Just looking? Open the web UI on a made-up example graph:

npx -y memory-lean --ui --demo

Setup for each agent

AgentServer configInstructions
Claude Codepluginincluded in the plugin
Xiaomi MiMo Codemimocode.jsoncskill or AGENTS.md
opencodeopencode.jsonAGENTS.md
OpenAI Codex CLIcodex mcp addAGENTS.md
Cursor.cursor/mcp.jsonAGENTS.md or a rule
VS Code (Copilot).vscode/mcp.jsoncopilot-instructions.md
Gemini CLIsettings.jsonGEMINI.md
Windsurfmcp_config.jsona rule
Clinecline_mcp_settings.json.clinerules/
Zedsettings.jsonAGENTS.md or .rules
JetBrains IDEsAI Assistant settingsa rule or guidelines
Claude Desktopclaude_desktop_config.jsonproject instructions

The graph is created on the first write at ~/.claude/memory-graph/memory.jsonl, whichever agent writes it, so all your agents share one memory. Set MEMORY_FILE_PATH to keep it somewhere else.

Web UI

npx -y memory-lean --ui

This opens your memory in the browser. Everything an agent can do, you can do here:

  • Explore. Each type gets its own bubble. Click an entity to highlight everything it connects to, drag nodes to arrange them, and scroll to zoom. Search matches names, types and facts.
  • Edit. Add, edit and delete facts, rename an entity or change its type, add and remove relations, create and delete entities, and restore archived facts. Every change passes the same checks as the agents' tools.
  • Watch. Changes your agents make appear within two seconds.
  • Spot problems. The overview lists pending work, the most connected entities, and anything over budget, which is also marked on the graph.

Follow the connections. Select an entity to see its facts and relations. Find anything. Search names, types and facts at once.

Edit in place. With the same 300-character limit the agents have. Light or dark. It follows your system, or pick one.

The page runs on your machine only (127.0.0.1) and needs the one-time key in the link it prints, so other websites cannot read or change your memory. Nothing is uploaded anywhere.

How it works

Search, then open

The reference server answers a search with every matching entity in full, as pretty-printed JSON. memory-lean answers with a ranked list of names and the lines that matched:

> search_nodes { "query": "deploy" }

57 match "deploy", top 10 shown (narrow the query or raise limit). open_nodes for full entities.

  • shop-backend [service] 12 obs, 6 rel › 2026-03-02: deployed 2.4.0 to production › deploy with scripts/release.sh, never by hand
  • PENDING shop-backend 2.4.0 [pending] 2 obs, 3 rel › …mobile apps still call the old endpoint until the deploy of 2.4.0 reaches them

The agent then opens only what it needs:

> open_nodes { "names": ["shop-backend"] }

shop-backend [service] (3 archived)

  • NestJS API behind api.example.com
  • 2026-03-02: deployed 2.4.0 to production

relations

shop-app -talks_to-> shop-backend PENDING shop-backend 2.4.0 -blocks-> shop-app

Why it stays lean
LimitWhat it means
Small answerssearch_nodes returns at most 10 names with snippets, read_graph returns an index of names, and only open_nodes returns full entities.
Short factsAn observation longer than 300 characters is rejected, with a message telling the agent to split it or put the detail in the repo.
A cap per entityAn entity keeps 15 observations. Past that, the oldest dated ones move to archive/ .md. Nothing is deleted: they can be listed and restored, and undated facts (the identity facts) always stay.
Search that narrowsEvery word must match somewhere in the entity, so adding a word narrows the result. The reference server looks for the query as one exact phrase.
How it keeps your data safe
SafeguardWhat it means
Safe to shareWriters take a lock file, so several agent sessions can use one graph without overwriting each other. Every write replaces the file atomically.
Daily backupsA copy goes to backups/ once a day; the last 7 are kept.
Damaged lines are keptA line that cannot be read is moved to memory.jsonl.unreadable on the next write and reported, never silently dropped.
Plain filesThe graph is JSON lines, archives are Markdown, backups are copies. You can read, grep and edit all of it by hand.

Tools

ToolWhat it returns
search_nodesRanked list of entity names with counts and up to two matching snippets each. Every word must match the name, type, an observation, or the type of a relation touching the entity.
open_nodesThe full entities you name, as compact text, with every relation touching them and their archive count. Unknown names come back with "did you mean" suggestions.
read_graphAn index: entity names grouped by type, with observation counts. Never the observations.
create_entitiesCreates entities; existing names are skipped.
create_relationsCreates relations between existing entities; duplicates are skipped.
add_observationsAdds facts to an entity, enforcing the length limit and the per-entity cap.
delete_observationsRemoves observations by exact text.
delete_relationsRemoves specific relations.
delete_entitiesRemoves entities and every relation touching them.
rename_entityRenames an entity, keeping its observations, relations and archive. *Not in the reference server.*

| archived_observations | Lists what was archived for an entity, optionally filtered, and restores chosen fa

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

Ask PopNx