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4q Tokenz

by steveweltmanversion 1.14.1i★ –iRuns on your computer
Registry nameio.github.steveweltman/4q-tokenz

Install

Overview

Description from the maker (original English)

Intelligent MCP proxy that reduces token usage by exposing only mcp_search and mcp_call.

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": {
    "4q-tokenz": {
      "command": "npx",
      "args": [
        "-y",
        "4q-tokenz"
      ]
    }
  }
}

Run this in your terminal

claude mcp add 4q-tokenz -- npx -y 4q-tokenz

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "4q-tokenz": {
      "command": "npx",
      "args": [
        "-y",
        "4q-tokenz"
      ]
    }
  }
}

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": {
    "4q-tokenz": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "4q-tokenz"
      ]
    }
  }
}

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 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account steveweltman, 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 5684 servers in this category
  • Published to the registry more recently than 12% of the other 5684 servers in this category
  • Basic checks equal to or better than 100% of the other 5684 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 4q Tokenz 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 (1.14.1) reached the registry 6 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:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 972.7K/wk★ 64.2KUpdated 2 days ago

Computer or cloud

Codebase Memory

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

by DeusDataWidely used↓ 18K/wk★ 48.1KUpdated 22 days ago

Runs on your computer

Exa

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

by exa-labsGrowing★ 5.2KUpdated 2 months ago

Runs in the cloud✓ exa.ai

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.

MCP Proxy Gateway

A context-aware MCP proxy that reduces token usage by exposing only 3 tools (mcp_search, mcp_call, mcp_schema) to LLMs instead of the full catalog.

Why This Exists

When you connect multiple MCP servers to an LLM, every tool from every server is listed in the LLM's context window. For a typical workspace with 50-100 tools across multiple MCP servers, that's thousands of tokens of schema documentation on every request.

MCP Proxy Gateway sits between your LLM and your MCP servers, offering:

  • JIT tool loading — tools from upstream servers are discovered once at startup, then tools are called on-demand. Clients never see the full catalog.
  • Intelligent search — fast lexical (BM25) search to find the right tool for a query. Tool tokens are pre-computed at startup for zero-overhead per-query scoring.
  • Token savings — LLMs only see 3 tool schemas (search, call, schema) instead of 50+. Typical savings: 20-40% per turn for tool-heavy workflows.
  • Zero native dependencies — pure JavaScript, no native modules, no model downloads, no supply chain risk from ML packages.
┌─────────────────────────────────────────────────────────────────┐

│ Your LLM │ │ (sees only: mcp_search, mcp_call, mcp_schema) │ └────────────────────┬────────────────────────────────────────────┘ │ ┌───────────▼──────────────┐ │ MCP Proxy Gateway │ │ ┌──────────────────────┐ │ │ │ Tool Registry │ │ │ │ (BM25 lexical) │ │ │ └──────────────────────┘ │ │ ┌──────────────────────┐ │ │ │ Connector Manager │ │ │ │ (Idle timeout reap) │ │ │ └──────────────────────┘ │ └────────────┬─────────────┘ │ ┌─────────────┼─────────────┐ │ │ │ ▼ ▼ ▼ ┌─────────┐ ┌─────────┐ ┌─────────┐ │Google │ │MailerLite│ │Your Svc │ │Gmail │ │ Campaigns│ │ Custom │ │Calendar │ │ │ │ Tools │ │Drive │ │ │ │ │ └─────────┘ └─────────┘ └─────────┘

Prerequisites

  • Node.js 18+ with npm or pnpm
  • One or more MCP servers to proxy (stdio or HTTP)

Installation

From Source
git clone https://github.com/steveweltman/4q-tokenz.git

cd 4q-tokenz

pnpm install pnpm build

Install to ~/.local/bin and configure

./install.sh

As a Dependency
npm install -g 4q-tokenz

Getting Started: Google Workspace Example

Here's a concrete walkthrough to connect Google Workspace (Gmail, Calendar, Drive) to your LLM through the proxy:

Step 1: Choose or Build an MCP Server for Google

You need an MCP server that wraps Google APIs. Options:

  • @antidrift/mcp-google (recommended) — A collection of MCP server implementations for Google Workspace (Gmail, Calendar, Drive, Docs, Sheets). Works out of the box with this proxy.
  npm install @antidrift/mcp-google

or

npx @antidrift/mcp-google --help

  • @modelcontextprotocol/server-gmail — Gmail-only, official MCP server
  • Build your own — See the MCP spec to wrap your own APIs
Step 2: Set Up Google OAuth
  1. Go to Google Cloud Console
  2. Create a new project or select an existing one
  3. Enable these APIs:
  • Gmail API
  • Google Calendar API
  • Google Drive API
  1. Create an OAuth 2.0 credential (type: Desktop application)
  2. Download the credential JSON
  3. Run the Google MCP server once to generate token.json:
   GOOGLE_CREDENTIAL_FILE=~/Downloads/credentials.json \

npx @antidrift/mcp-google

   This opens a browser for you to authorize. Once done, it saves `token.json` locally.
Step 3: Configure the Proxy

Create ~/.config/4q-tokens/config.json:

{

"upstreams": [ { "name": "google-workspace", "transport": "stdio", "command": "npx", "args": ["@antidrift/mcp-google"], "env": { "GOOGLE_TOKEN_FILE": "~/.local/share/google-mcp/token.json", "GOOGLE_CONNECTORS": "gmail,calendar,drive" } } ], "searchLimit": 5, "callItemLimit": 30, "maxTextLength": 800, "maxOutputTokens": 10000, "idleTimeoutMs": 600000 }

Step 4: Start the Proxy
mcp-proxy

Or via systemd if installed:

systemctl --user start mcp-proxy

Step 5: Connect Your LLM

Configure your LLM to use http://127.0.0.1:9200/mcp as its MCP server. It will see:

  • mcp_search — find tools by natural language
  • mcp_call — invoke a tool
  • mcp_schema — see tool details

Example query:

mcp_search("send an email")

Returns: google_send_email (Gmail)

mcp_call(ref="google_send_email", args={"to": "user@example.com", "subject": "Hello", "body": "Test"})

Configuration

Quick Start with Environment Variables
export MCP_PROXY_UPSTREAMS='[

{ "name": "google", "transport": "stdio", "command": "node", "args": ["/path/to/google/server.mjs"], "env": { "GOOGLE_TOKEN_FILE": "token.json" } } ]'

export MCP_PROXY_SINGLETON_PORT=9200 export MCP_PROXY_DASHBOARD_PORT=9100

node dist/index.js

Config File (Recommended)

Create ~/.config/4q-tokens/config.json:

{

"upstreams": [ { "name": "google-workspace", "transport": "stdio", "command": "npx", "args": ["@antidrift/mcp-google"], "env": { "GOOGLE_TOKEN_FILE": "token.json", "GOOGLE_CONNECTORS": "gmail,calendar,drive" } }, { "name": "external-api", "transport": "http", "url": "https://mcp.example.com/", "auth": { "apiKey": "MY_API_KEY_ENV_VAR" } } ], "searchLimit": 3, "callItemLimit": 20, "maxTextLength": 500, "maxOutputTokens": 8000, "idleTimeoutMs": 300000 }

Then run:

node dist/index.js

The proxy will load the config from ~/.config/4q-tokens/config.json if it exists, otherwise fall back to the MCP_PROXY_UPSTREAMS environment variable.

Configuration Reference
Upstream Server Config
{

"name": "unique-id", "transport": "stdio" | "http",

// For stdio transport: "command": "node", "args": ["path/to/server.mjs"], "cwd": "/working/dir", // optional "env": { "KEY": "value" }, // optional

// For http transport: "url": "https://example.com/mcp", "auth": { "apiKey": "ENV_VAR_NAME" // reads from process.env[ENV_VAR_NAME] } }

Proxy Options
OptionDefaultDescription
searchLimit3Max tools returned by mcp_search
callItemLimit20Max items in mcp_call response
maxTextLength500Truncate text fields to N chars (detail=false: 500, detail=true: 1500)
maxOutputTokens8000Hard cap on response size
idleTimeoutMs300000Disconnect upstream servers after N ms of inactivity (0 = disabled)

Environment variable overrides:

export MCP_PROXY_SEARCH_LIMIT=5

export MCP_PROXY_CALL_ITEM_LIMIT=30 export MCP_PROXY_MAX_TEXT_LENGTH=800 export MCP_PROXY_MAX_OUTPUT_TOKENS=10000 export MCP_PROXY_IDLE_TIMEOUT_MS=600000

Multi-Agent Lanes (Per-Agent Isolation)

When several agents share one proxy, each agent should only be able to see and call its own tools. 4Q-Tokenz does this with lanes. A lane is a named view of the tool registry that is served at its own URL, /mcp/ . An agent connected to its lane cannot discover or call tools from any other lane, even if it knows the ref.

agent hope    -> entry "tokens-hope"   -> /mcp/hope    -> google-hope, hope-memory

agent clark -> entry "tokens-clark" -> /mcp/clark -> google-clark, clark-memory (no lane) -> /mcp -> refused (HTTP 403)

Defining lanes

Add an agents block next to upstreams in ~/.config/4q-tokens/config.json (or set MCP_PROXY_AGENTS as JSON). Each lane lists the upstream providers it may use and, optionally, individual tools to deny:

{

"upstreams": [ ... ], "agents": { "hope": { "allow": ["google-hope", "hope-memory"], "deny": ["google-hope.drive_share", "google-hope.share_doc"] }, "clark": { "allow": ["google-clark", "clark-memory"] } } }

FieldDescription
allowUpstream provider names this lane may use (required, at least one)
denyOptional. provider.tool or *.tool entries removed from the lane after allow is applied. Deny always wins. A deny entry that matches no tool logs a warning at startup, so typos do not fail open silently

Agent ids must match ^a-z0-9_{0,63}$. The plain array form ("hope": ["google-hope"]) is still accepted and means allow-only.

Fail-closed behavior
  • The unscoped route /mcp is refused with 403. A client that is not bound to a lane never sees the whole tool pool. For local development only, set MCP_PROXY_ALLOW_UNSCOPED=1 to re-enable it.
  • An unknown lane (/mcp/nobody) returns 404.
  • A stdio instance that would become the primary (and so serve the whole pool to one client) refuses to start unless MCP_PROXY_ALLOW_UNSCOPED=1. Run the proxy as a service instead (see Singleton and Bridge Mode).
  • A bridge refuses to start without a valid MCP_PROXY_AGENT.
Singleton and Bridge Mode

One primary instance owns the upstream connections and listens on MCP_PROXY_SINGLETON_PORT (default 9200). Run it as a service with MCP_PROXY_SERVICE_MODE=1 (HTTP only, no stdio). Any additional instance launched as a stdio MCP server detects the live primary through the lock file and becomes a bridge. A bridge forwards the client's stdio traffic to the primary on its own lane:

MCP_PROXY_AGENT=hope node dist/index.js    # bridge: forwards to http://127.0.0.1:9200/mcp/hope

The lock file lives in MCP_PROXY_LOCK_DIR, else $XDG_RUNTIME_DIR, else /run/user/ , else the temp dir. Hosts that launch the proxy with a minimal environment (for example the OpenClaw gateway) do not set XDG_RUNTIME_DIR, which is why the /run/user/ fallback exists. If an instance wins a lock but finds the port already served, it releases the lock and bridges instead of crashing.

Wiring agents in OpenClaw

OpenClaw has no per-agent MCP setting and does not tell a stdio server which agent launched it. Isolation therefore needs two layers:

  1. One MCP server entry per agent, each passing its own lane through the environment. Use names that start with a letter, because OpenClaw exposes MCP tools as __ :
"mcp": {

"servers": { "tokens-hope": { "command": "/path/to/start-4q-tokens.sh", "env": { "MCP_PROXY_AGENT": "hope" } }, "tokens-clark": { "command": "/path/to/start-4q-tokens.sh", "env": { "MCP_PROXY_AGENT": "clark" } } } }

  1. Each agent denies the other agents' entries using glob patterns in its tool policy, so it does not see them at all (deny always wins in OpenClaw's tool policy):
"agents": { "entries": { "hope": { "tools": { "deny": ["tokens-clark__*"] } } } }

The proxy lane is the enforcing boundary: whatever an agent does, a bridge bound to hope can only reach /mcp/hope. The OpenClaw deny list is defense in depth that keeps one agent from being handed another agent's entry.

Verifying isolation
  • Proxy log: every session is logged with its lane, for example HTTP session created: ... [hope]. There should be no [open] sessions and no Refused unscoped lines in normal operation.
  • From each agent, run mcp_search and confirm only that lane's providers appear.
  • From an agent, call a ref from another lane. It must return Tool not found.

Running

Standalone (Stdio Transport)
node dist/index.js

The proxy connects vi

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