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

Khwan

by khwanlabsversion 0.3.12i★ –iComputer or cloud
Registry nameai.khwan/khwan-mcp

Install

Overview

Description from the maker (original English)

Durable AI memory: recall distilled facts in a later session or subagent, and remember new ones.

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: Computer or cloud
  • Transport: stdio, Streamable HTTP
  • Category: Search & AI memory
  • You need to fill in: KHWAN_API_KEY

Install

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

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on the maker’s server: what you ask it goes through their server.
  • You fill in yourself: KHWAN_API_KEY, KHWAN_CORE, KHWAN_USER, KHWAN_BASE_URL

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • Runs in the cloudNothing to install; it connects over the internet
  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

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

Works in Claude on the web, desktop and mobile:

  1. Open Settings → Connectors
  2. Press Add custom connector
  3. Paste the address below and press Add
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Add2https://…3
https://mcp.khwan.ai/mcp/{core}/{user}

The address contains {…} parts that only you know (such as your account), so copy it and fill them in.

Or run it on your computer

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

{
  "mcpServers": {
    "khwan": {
      "command": "uvx",
      "args": [
        "khwan-mcp"
      ],
      "env": {
        "KHWAN_API_KEY": "your-value",
        "KHWAN_CORE": "your-value",
        "KHWAN_USER": "your-value",
        "KHWAN_BASE_URL": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add --transport http khwan 'https://mcp.khwan.ai/mcp/{core}/{user}'

Or run it on your computer

claude mcp add khwan --env KHWAN_API_KEY=your-value --env KHWAN_CORE=your-value --env KHWAN_USER=your-value --env KHWAN_BASE_URL=your-value -- uvx khwan-mcp

Fill in the empty values before running it.

The address contains {…} parts that only you know (such as your account), so copy it and fill them in.

Or copy the settings yourself

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

{
  "mcpServers": {
    "khwan": {
      "url": "https://mcp.khwan.ai/mcp/{core}/{user}"
    }
  }
}

Or run it on your computer

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "khwan": {
      "command": "uvx",
      "args": [
        "khwan-mcp"
      ],
      "env": {
        "KHWAN_API_KEY": "your-value",
        "KHWAN_CORE": "your-value",
        "KHWAN_USER": "your-value",
        "KHWAN_BASE_URL": "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.

The address contains {…} parts that only you know (such as your account), so copy it and fill them in.

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "khwan": {
      "type": "http",
      "url": "https://mcp.khwan.ai/mcp/{core}/{user}"
    }
  }
}

Or run it on your computer

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "khwan": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "khwan-mcp"
      ],
      "env": {
        "KHWAN_API_KEY": "your-value",
        "KHWAN_CORE": "your-value",
        "KHWAN_USER": "your-value",
        "KHWAN_BASE_URL": "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.

ChatGPT connects only to servers on the internet:

  1. Open ChatGPT on the web → Settings → Connectors (Apps)
  2. Press Create or Add (some plans need Developer mode under Advanced first)
  3. Paste the address below, give it a name and save
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Create2https://…3
https://mcp.khwan.ai/mcp/{core}/{user}

The address contains {…} parts that only you know (such as your account), so copy it and fill them in.

Menu names can differ slightly by plan and over time.

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

Values you fill in

  • KHWAN_API_KEY secret required env
    Your Khwan key from https://app.khwan.ai (kwk_live_...). It authenticates you to Khwan; it is not your model provider's key.
  • KHWAN_CORE env
    Select a named core (brain). Paid plans only — the free plan has just `default`, and an unknown slug answers 404. Leave unset to use the default.
  • KHWAN_USER env
    A separate brain inside the core, created on first write — 3 on the free plan, unlimited on paid. Sets the X-Khwan-User header.
  • KHWAN_BASE_URL env
    Override the API base URL, e.g. http://127.0.0.1:8010 for a self-hosted engine.

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

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

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 against the domain khwan.ai (the registry checks domain ownership)

  • … 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

    The address needs your own account values, so we cannot check it for you

  • – Not applicable

    Sign-in with OAuth

    The address needs your own account values, so we cannot check it for you

  • … Not checked yet

    No hidden instructions in tool descriptions

    Not checked yet; we read the tool list when we check the endpoint

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7249 servers in this category
  • Published to the registry more recently than 34% of the other 7249 servers in this category
  • Basic checks equal to or better than 100% of the other 7249 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 Khwan 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?

You need to fill in: KHWAN_API_KEY

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.12) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

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.

khwan-mcp

Durable memory that survives the session. An MCP server that plugs Khwan — a pure AI-memory layer — into Claude Code, Claude Desktop, or any MCP client.

Khwan never runs *your* model. The client is the model. Its job is to persist and distil what matters into a brain you can recall in a later session or seed a subagent with — a compact, bounded set of facts instead of a replayed transcript. One account can hold many isolated cores (brains), and — on paid plans — an isolated sub-brain per end-user.

Nothing on the read or write path costs you an inference call: khwan_recall and khwan_remember make none. Khwan does run one model of its own, on a schedule — a nightly pass that distils stored turns into standing lessons. A real production run was 8 brains and 245 stored turns distilled into 11 lessons, for $0.0094. That pass is Khwan's cost, not yours, and it is the whole difference from memory layers that compress, graph, or consolidate on every turn.

How it saves tokens (and where it doesn't)

Be honest about the mechanism — an MCP adds to a host's context, it cannot replace the transcript the host already sends. So:

  • Within one hot session, it does not save tokens. Claude Code caches its growing history (cache reads ≈ 0.1×), so re-injecting memory every turn only adds. Don't do that here.
  • Across sessions and subagents, it does. A cache dies in minutes; a session ends. Khwan persists distilled facts so the *next* run recalls them cheaply — no cold-replay of an old transcript, and facts that already scrolled out of context are retrievable again.

The token-smart pattern: seed once, remember durable facts (below), rather than running the full loop on every turn of a caching host. The full prepare → record loop still shines in a custom agent on a non-caching host, where replacing history with distilled memory bounds per-turn cost directly.

Install

pip install khwan-mcp          # or: uvx khwan-mcp

Connect to Claude Code

claude mcp add khwan --scope project \

-e KHWAN_CORE=default \ -- khwan-mcp

--scope project writes .mcp.json into the repo, so the setting travels with the project. Note what is not in that command: the key.

Keeping the key out of the repo

claude mcp add -e KHWAN_API_KEY=… writes the literal value into .mcp.json — a file whose whole point is being committed. Two ways to avoid that, and the second is the one that works everywhere:

Shell environment. Leave KHWAN_API_KEY out of the config entirely and export it in the shell that launches claude. The server inherits it.

export KHWAN_API_KEY=kwk_live_xxx

A launcher (works in the desktop app too). A desktop app is started from a dock or menu, not a login shell, so it inherits none of your shell exports and the approach above silently yields no key. Read it from a file instead:

mkdir -p ~/.khwan && chmod 700 ~/.khwan

printf 'KHWAN_API_KEY=kwk_live_xxx\n' > ~/.khwan/env && chmod 600 ~/.khwan/env

cat > ~/.khwan/khwan-mcp <<'SH' #!/bin/sh set -a [ -f "$HOME/.khwan/env" ] && . "$HOME/.khwan/env" set +a exec khwan-mcp "$@" SH chmod 700 ~/.khwan/khwan-mcp

Then point the config at the launcher and keep only non-secret settings inline:

claude mcp add khwan --scope project \

-e KHWAN_CORE=acme -e KHWAN_USER=Web \ -- ~/.khwan/khwan-mcp

.mcp.json is now safe to commit, and every new repo costs two lines instead of a pasted key. Anyone else on the team writes their own ~/.khwan/env.

One brain per project

Memory is only useful if the right project's memory comes back. Two axes, and both give complete isolation:

selected byfreepaid
coreKHWAN_CORE1 — default only5 (starter) → 25 (pro)
sub-brainKHWAN_USER3unlimited

A sub-brain is a full separate brain, not a filter: account::@web shares nothing with account::@api. So the two axes multiply, and a free account already holds four isolated brains — the core on its own, plus three sub-brains:

account              default core, no KHWAN_USER      brain 1

account::@web KHWAN_USER=web brain 2 account::@api KHWAN_USER=api brain 3 account::@docs KHWAN_USER=docs brain 4

Which means one-brain-per-project works on the free plan, for up to four projects — and it needs no `KHWAN_CORE` at all:

# in ~/code/web

claude mcp add khwan --scope project -e KHWAN_USER=web -- ~/.khwan/khwan-mcp

in ~/code/api

claude mcp add khwan --scope project -e KHWAN_USER=api -- ~/.khwan/khwan-mcp

Named cores are the paid axis. Reach for one when four brains stop being enough, or when you want them grouped per client rather than per repository:

# in ~/code/acme-web

claude mcp add khwan --scope project -e KHWAN_CORE=acme -e KHWAN_USER=Web -- ~/.khwan/khwan-mcp

in ~/code/acme-api

claude mcp add khwan --scope project -e KHWAN_CORE=acme -e KHWAN_USER=Api -- ~/.khwan/khwan-mcp

Two things to know before you point KHWAN_CORE anywhere. A core must exist first — an unknown slug answers 404, not "created it for you" — and they are created in the dashboard. On the free plan there is nothing to point at: the cap of one is spent on default, so creating a named core answers 402. Leave KHWAN_CORE unset there and use KHWAN_USER. Sub-brains, by contrast, are created on first write.

Recommended pattern (token-smart)

On a caching host like Claude Code, prefer seed + remember over the per-turn loop:

  1. Seed at the start of a session or subagent:

"Call khwan_recall(query=" ") and use the returned seed_text as

context."

  1. Remember durable facts as they emerge:

"That's a standing decision — call khwan_remember(fact="…")."

Reinforce it in your project's CLAUDE.md, e.g.:

- At the start of a task, call `khwan_recall` to seed relevant memory.
  • When a durable decision/preference/fact emerges, call khwan_remember.
  • Don't call prepare/record every turn — it adds tokens without saving them here.

Seeding a subagent is where the win is clearest — hand it a bounded brief instead of the whole transcript:

"Recall deploy memory with khwan_recall(query="deploy runbook"), then spawn a

subagent whose brief is that seed_text plus the task."

Connect to Claude Desktop

Claude Desktop and Claude Code keep separate MCP configuration — a server added to one is invisible to the other, and claude mcp add does not touch this file. Add to claude_desktop_config.json:

{

"mcpServers": { "khwan": { "command": "/Users/you/.khwan/khwan-mcp", "env": { "KHWAN_CORE": "acme", "KHWAN_USER": "Web" } } } }

Use an absolute path: a desktop app does not get your shell's PATH either, so a bare khwan-mcp may not resolve. One core is selected for the whole app — there is no per-project switch here, so choose a broad one.

Configuration (environment)

VarRequiredPurpose
KHWAN_API_KEYyesYour key from the Khwan dashboard (kwk_live_…).
KHWAN_COREnoSelect a named core. Paid plans only — free has just default.
KHWAN_USERnoA separate brain inside the core — 3 on free, unlimited on paid.
KHWAN_BASE_URLnoOverride the API base — e.g. http://127.0.0.1:8010 for a local engine.

Tools

ToolWhen
khwan_recall(query, limit=3)seed a session/subagent — synthesised lessons + up to 3 relevant facts, as seed_text.
khwan_remember(fact)persist a durable fact/preference for future sessions.
khwan_prepare(input)full loop, before answering — memory context + a turn_token.
khwan_record(turn_token, answer)full loop, after answering — persists the turn so Khwan learns.
khwan_memory(limit=20)inspect what the brain currently remembers.
khwan_cores()list the isolated cores on the account.

khwan_recall / khwan_remember are the token-smart pair for a caching host; khwan_prepare / khwan_record are the full loop for custom agents (pass the exact turn_token from prepare back into record).

What comes back, and what an empty answer means

khwan_recall returns at most three facts — that ceiling is the server's, so limit can lower it but not raise it — plus any lessons synthesis has distilled from many past turns. Lessons lead the seed_text: a rule earned over months outranks a single turn that happens to sit nearby in the index.

Retrieval applies a relevance floor, so an empty `facts` is an answer: the brain has nothing close to this question. Read it as "not known here" rather than as a failure, and do not fill the gap by leaning on whichever fact was nearest.

The floor is deliberately loose, because a memory wrongly dropped is invisible while a memory wrongly kept is not. Expect a returned fact to be *plausibly* related, not certainly relevant — read it before relying on it.

Seeding a brain from work you have already done

A new brain knows nothing, so its first weeks of recall are thin — while the answers are often already sitting in the host's own transcripts, unread. examples/backfill/ replays Claude Code transcripts into a brain: deterministic, no model calls, dry-run by default.

python3 examples/backfill/backfill_claude_code.py --map cores.json

Always-on memory (Claude Code hooks)

The tools above are called *when Claude decides to*. For deterministic memory — no reliance on the model — use the hook preset in examples/claude-code-hooks/: a UserPromptSubmit hook injects memory on every prompt and a Stop hook records every answer.

⚠️ On a caching host this is the *thorough* option, not the *cheap* one — it

adds per-turn tokens. Prefer it when recall reliability matters more than token

cost (or on a non-caching client); otherwise use khwan_recall at session

start.

Source

github.com/khwanlabs/khwan-mcp — this server runs on your machine, with your key, reading what you type. Read it before you install it.

License

MIT — © Khwan Labs. See LICENSE.

Ask PopNx