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PopNx MCPMCP servers for people who use AI · explained in plain words

Tokenectomy Razor

by Tokenectomy-Labsversion 1.3.3i★ –iRuns on your computer
Registry nameio.github.Tokenectomy-Labs/razor

Install

Overview

Description from the maker (original English)

Cut 95% of framework noise and token bloat from error logs for AI agents.

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: Other

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": {
    "razor": {
      "command": "npx",
      "args": [
        "-y",
        "tokenectomy-razor"
      ]
    }
  }
}

Run this in your terminal

claude mcp add razor -- npx -y tokenectomy-razor

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "razor": {
      "command": "npx",
      "args": [
        "-y",
        "tokenectomy-razor"
      ]
    }
  }
}

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": {
    "razor": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "tokenectomy-razor"
      ]
    }
  }
}

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 Tokenectomy-Labs, 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 Otheri

  • More stars than 0% of the other 32606 servers in this category
  • Published to the registry more recently than 45% of the other 32606 servers in this category
  • Basic checks equal to or better than 100% of the other 32606 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 Tokenectomy Razor 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 (1.3.3) 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. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Georgia MCP

Alternatives

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

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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Georgia MCP

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An MCP server for Georgian public data, read from the organizations that publish it.

Computer or cloudUpdated today
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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.

Tokenectomy Razor

Fix Claude Code & Cursor Rate Limits: Zero-Latency Local AI Gateway & Context-Surgery MCP Server in Rust Stop burning 20,000 tokens on node_modules stack traces. Tokenectomy Razor is a sub-millisecond local AI Gateway reverse proxy (127.0.0.1:8080) & companion MCP server written in safe Rust. Excises 41.7%–99.7% framework noise from terminal error logs, redacts leaked DB credentials/JWTs, and caches prompts for free.

Quick Start (10s) • Architecture • The Problem • Before & After • Live Interactive Demo • Benchmarks

                                 ┌────────────────────────────────────────────────────────┐

│ Autonomous Agents │ │ Claude Code • Cursor • Antigravity • Cline • Windsurf │ └───────────────────────────┬────────────────────────────┘ │ ▼ (HTTP / SSE Outbound Prompts) ┌──────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐ │ ⚡ TOKENECTOMY AI GATEWAY (127.0.0.1:8080) │ │ │ │ ┌─────────────────────────┐ ┌───────────────────────────┐ ┌──────────────────────────────────────────────┐ │ │ │ Zero-Cost Prompt │ │ Zero-Leak Credential │ │ Polyglot Trace Surgery │ │ │ │ Cache │ │ Redaction │ │ (9 Languages) │ │ │ │ <1ms Hit • 100% Free │ │ API Keys • JWTs • DB URIs│ │ node_modules • site-packages • .cargo │ │ │ └───────────┬─────────────┘ └─────────────┬─────────────┘ └──────────────────────┬───────────────────────┘ │ │ │ │ │ │ │ └───────────────────────────────┼────────────────────────────────────────┘ │ │ ▼ │ │ Smart Upstream Auto-Router │ │ (Anthropic • OpenAI • Groq • Ollama Local) │ └──────────────────────────────────────────────┬───────────────────────────────────────────────────────────────────┘ │ ┌────────────────────────────────┼────────────────────────────────┐ ▼ ▼ ▼ api.anthropic.com api.openai.com localhost:11434 (Claude 3.5 / 3.7 Sonnet) (GPT-4o / o1 / o3-mini) (DeepSeek / Llama)


⚡ Quick Start (10s)

0. Zero-Config One-Liner Wrapper (wrap)

Run any coding agent or test suite directly behind Tokenectomy's privacy & caching gateway with zero manual environment variable setup:

# Wrap Claude Code CLI

razor wrap -- claude

Wrap Aider with DeepSeek or Ollama (Auto-Transpiled on the fly!)

razor wrap -- aider --model deepseek/deepseek-chat

Wrap test runs to scrub logs and prevent accidental credential leakage

razor wrap npm test

1. Launch the Standalone AI Gateway (Manual Mode)
npx -y tokenectomy-razor --proxy

💡 Smart Multi-Provider Auto-Routing & Universal LLM Transpiler ON by default! Tokenectomy automatically analyzes request paths and headers. Need to run Claude Code against DeepSeek or Ollama? Tokenectomy transparently transpiles Anthropic /v1/messages format into OpenAI /v1/chat/completions on-the-fly and vice-versa.

2. Connect Your Favorite Agent

Point your coding agent or CLI to the local gateway on 127.0.0.1:8080:

Agent / EnvironmentSetup Command or ConfigurationAuto-Routed Upstream
Claude Codeexport ANTHROPIC_BASE_URL="http://127.0.0.1:8080"https://api.anthropic.com
CursorModels > OpenAI Base URL: http://127.0.0.1:8080/v1https://api.openai.com
Google Antigravity / Geminiexport OPENAI_BASE_URL="http://127.0.0.1:8080/v1"https://api.openai.com
Cline / Roo CodeProvider: OpenAI Compatible &bull; Base URL: http://127.0.0.1:8080/v1https://api.openai.com
Ollama / Local LLMsBase URL: http://127.0.0.1:8080http://localhost:11434
3. Real-Time FinOps & Security Dashboard

Open `http://127.0.0.1:8080/dashboard` in your browser to observe live token reductions, prompt cache hits, dollar savings, and redacted credentials in real time.


4. Companion MCP Server Setup (Sub-Cortex)

For agents calling deep diagnostic tools (get_error_context, analyze_code, apply_code_patch):

Claude Code CLI
claude mcp add tokenectomy npx -y tokenectomy-razor --mcp
Google Antigravity / Gemini CLI
agy mcp add tokenectomy-razor -- npx -y tokenectomy-razor --mcp
Cursor Composer (.cursor/mcp.json)
{

"mcpServers": { "tokenectomy": { "command": "npx", "args": ["-y", "tokenectomy-razor", "--mcp"] } } }

Claude Desktop (claude_desktop_config.json)
{

"mcpServers": { "tokenectomy": { "command": "npx", "args": ["-y", "tokenectomy-razor", "--mcp"] } } }

5. Terminal Piping & CLI Scrubbing
npm test 2>&1 | npx tokenectomy-razor

🛑 The Problem: Why Your AI Hits Rate Limits & Hallucinates

When your app crashes during development (Next.js, Express, FastAPI, Tokio), the runtime dumps hundreds of lines of third-party plumbing from node_modules or site-packages.

When you paste that raw crash dump into Cursor or Claude:

  1. Eats Your 5-Hour Rate Limit: A single Express/Prisma error can dump 5,000 to 45,000 tokens of third-party library code you never wrote. A few crash loops easily burn your session limit.
  2. Triggers AI Hallucinations: Claude gets lost in framework internals (node_modules/express/lib/router/layer.js or starlette/routing.py) and tries to edit library files instead of your actual application code.
  3. Leaks Secrets & Credentials: Connection strings with raw database passwords, JWT bearer tokens, and cloud keys embedded in error traces get forwarded to external model servers.
Raw Terminal Crash (45,820 tokens + Leaked Secrets)

│ ▼ <0.2ms Local Rust DFA Engine [Redact Passwords & Keys] ──► [Strip Third-Party Framework Frames] ──► [Isolate Root Cause] │ ▼ Clean Context (118 tokens • Zero Secrets • Sub-millisecond)


🔍 Before & After Comparison

❌ Without Tokenectomy: AI Hallucinates & Burns Context
TypeError: Cannot read properties of undefined (reading 'token')

at loadComponents (/app/node_modules/next/dist/server/load-components.js:14:2) at renderToHTML (/app/node_modules/next/dist/server/render.js:50:5) at nextServer (/app/node_modules/next/dist/server/next-server.js:80:12) at processTicksAndRejections (node:internal/process/task_queues:95:5) at runMicrotasks (node:internal/process/task_queues:120:3) at checkoutHandler (/app/pages/api/checkout.ts:42:15) Database connection failed: postgresql://admin:super_secret_password@db.prod.internal:5432/primary API key leaked: [PopNx MCP ตัดค่าที่หน้าตาเหมือนกุญแจออก]

> **What Claude does:** Analyzes `load-components.js` and `next-server.js`, speculates on Webpack / Next.js internals, and leaks connection credentials to remote inference logs.
✅ With Tokenectomy: Clean Context & Instant Fix
// [Tokenectomy Surgery: 5 internal framework frames pruned (83.3%)]

// Source: /app/pages/api/checkout.ts:42:15 42 | const sessionToken = req.headers.authorization.token; | ^ TypeError: Cannot read properties of undefined (reading 'token') 🛡️ [CONNECTION_STRING_REDACTED] 🛡️ [ANTHROPIC_KEY_REDACTED]

> **What Claude does:** Instantly identifies that line 42 in `checkout.ts` attempted to access `.token` on undefined headers. Suggests optional chaining `req.headers.authorization?.token` immediately. Credentials redacted before transmission.

🔬 Verifiable Benchmarks

All performance claims are hardware-grounded and independently reproducible on physical hardware (measured on 10-Core Intel Core i5-1235U @ 15W running Arch Linux, Kernel 6.13):

Hardware Dependency Notice: Performance is hardware-dependent; reported throughput represents measured results on the specified test hardware (10-Core Intel Core i5-1235U @ 15W TDP). Throughput scales with higher TDP desktop/server CPUs and faster memory buses. Developers are encouraged to independently audit performance using the reproduction command below.

📋 Click to expand full raw benchmark terminal log ($ cargo test --release)

$ cargo test --release --test stress_benchmark -- --nocapture

===================================================================================== 🧪 TOKENECTOMY OSS VERIFIABLE HEAVY STRESS BENCHMARK (100% REPRODUCIBLE IN OSS) Hardware: 10-Core / 12-Thread Intel Core i5-1235U | OS: Arch Linux | Kernel Telemetry Active Initial Baseline Process Memory (VmRSS): 3.45 MB =====================================================================================

🔥 [TEST 1/3] QUARTER-MILLION LINES LOG REDACTION TORTURE (250,0

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

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