{"slug": "how-i-cut-45000-next-js-error-tokens-to-118-in-0-2ms-using-a-rust-mcp-server", "title": "How I Cut 45,000 Next.js Error Tokens to 118 in <0.2ms Using a Rust MCP Server", "summary": "A developer built an open-source Rust Model Context Protocol (MCP) server called Tokenectomy Razor that strips framework internals from error logs and redacts secrets locally before they reach an LLM. The tool reduces a 45,820-token Next.js error dump to 118 tokens in under 0.2 milliseconds, running entirely over stdio with a 3.45 MB memory footprint. It also uses Tree-sitter AST verification to roll back invalid agent-generated code patches, and received a Grade A (4.7/5.0) from Glama.ai's Tool Definition Quality Score audit.", "body_md": "If you use Cursor, Claude Desktop, or Cline daily,\n\n  you have probably watched your rate limits evaporate\n\n  because of a single runtime crash.\n\n```\nA Next.js build fails or a Python script panics, and\n```\n\nyour terminal vomits 500 lines of stack traces. The\n\n  LLM eagerly ingests all 45,000 tokens of internal\n\n`node_modules` machinery, webpack bundles, and event\n\n  loop frames.\n\n```\nYou just paid $0.15 for an AI model to read code it\n```\n\ncan't edit, your prompt cache is wiped, and your agent\n\n  is now hallucinating because its context window is\n\n  full of garbage.\n\n```\nWorse, your terminal stderr probably just leaked\n```\n\n`DATABASE_URL=postgres://admin:password@...` straight\n\n  to an external API.\n\n```\nI got tired of paying for framework noise, so I\n```\n\nbuilt an open-source Rust Model Context Protocol (MCP)\n\n  server called **Tokenectomy Razor** to fix it locally\n\n  before logs ever touch the LLM.\n\n```\n## What is eating your context window?\n\nA typical Next.js error trace looks like this:\ntext\n    TypeError: Cannot read properties of undefined\n  (reading 'digest')\n        at Object.<anon> (/node_modules/next/bundle5.\n  js:142:31)\n        at __webpack_require__\n  (/node_modules/next/bundle5.js:198:12)\n        at Object.execute (/node_modules/next/dev-\n  server.js:412:19)\n        at processTicksAndRejections (task_queues:95:5)\n        Database connection failed:\n  postgresql://admin:super_secret_password@db.prod.\n  internal:5432/primary\n        API key leaked: sk-ant-api03-\n  abcdef1234567890abcdef1234567890\n        [... 480 internal dependency frames flooding\n  context ...]\n\n  Notice three things:\n\n  1. 98% of those frames are inside node_modules. Your\n  AI agent is not going to edit webpack's internal\n  bundle logic. It only cares about the one line in\n  src/components/Header.tsx:42 where you missed a\n  parenthesis.\n  2. The database password and API key are sitting\n  unmasked in plain text.\n  3. The raw token count for this single error dump was\n  45,820 tokens.\n\n  ## What happens after Tokenectomy runs\n\n  When the AI agent invokes get_error_context via MCP,\n  Tokenectomy intercepts the log, strips framework\n  internals, redacts all secrets locally using a\n  deterministic DFA regex, and grabs bounded source code\n  lines around the actual crash:\n\n    [:TOKENECTOMY:M2M_CONTROL_PLANE:v1.3.0]\n    [STATE=FRAMEWORK_NOISE_PURGED]\n    [STRATEGY_APPLIED=AGGRESSIVE]\n    [ORIGINAL_BYTES=45820 | CLEAN_BYTES=118 |\n  REDUCTION=99%]\n    [PRIMARY_CRASH_COORDINATES=src/components/Header.\n  tsx:42]\n\n  [COGNITIVE_DIRECTIVE=INSPECT_CALLER_AT_src/components/\n  Header.tsx:42]\n    [:END_CONTROL_PLANE]\n\n    src/components/Header.tsx:42:15 - SyntaxError\n      42 |   const user = useSession( ;\n         |                           ^ Expected ')'\n    🛡️ [CONNECTION_STRING_REDACTED]\n    🛡️ [REDACTED]\n  ANTHROPIC_API_KEY=[REDACTED_SECRET_KEY]\n\n  Final token count: 118 tokens.\n  Reduction: 99.7%.\n  Zero credentials leaked to the cloud.\n\n  ## Why Rust and why local-first?\n\n  I did not want another slow node script or cloud proxy\n  adding 300ms of network latency to an agent loop.\n\n  1. Sub-millisecond latency: The core log surgery and\n  secret redaction pipeline runs in <0.2 milliseconds on\n  an Intel i5 CPU.\n  2. Zero cloud leaks: It runs 100% locally over stdio.\n  Your error logs, environment variables, and\n  proprietary code never touch an external server.\n  3. AST verification & rollback: The apply_code_patch\n  tool parses modified code with Tree-sitter before\n  saving to disk. If the agent generates invalid syntax,\n  it immediately rolls back with zero dirty git diff.\n  4. Lightweight footprint: Baseline process memory is\n  3.45 MB VmRSS.\n\n  Glama.ai audited the server definition under their\n  Tool Definition Quality Score (TDQS) and awarded it\n  Grade A (4.7 / 5.0) across all tools.\n\n  ## How to set it up (Takes 30 seconds)\n\n  You don't need to install Rust or compile anything. We\n  distribute pre-built native binaries via npm for\n  Linux, macOS (Apple Silicon & Intel), and Windows.\n\n  Add this to your claude_desktop_config.json or Cursor\n  MCP settings:\n\n    {\n      \"mcpServers\": {\n        \"tokenectomy\": {\n          \"command\": \"npx\",\n          \"args\": [\"-y\", \"tokenectomy-razor\", \"--mcp\"]\n        }\n      }\n    }\n\n  Or if you prefer native cargo:\n\n    cargo install tokenectomy\n\n  Then configure:\n\n    {\n      \"mcpServers\": {\n        \"tokenectomy\": {\n          \"command\": \"razor\",\n          \"args\": [\"--mcp\"]\n        }\n      }\n    }\n\n  ## Open Source & Repositories\n\n  Everything is open source under the MIT license:\n\n  1. GitHub: https://github.com/Tokenectomy-\n  Labs/Tokenectomy\n  2. Glama: https://glama.ai/mcp/servers/Tokenectomy-\n  Labs/Tokenectomy\n  3. npm: https://www.npmjs.com/package/tokenectomy-\n  razor\n  4. crates.io: https://crates.io/crates/tokenectomy\n\n  Give it a run next time your agent is about to eat a\n  40,000-token crash log. Your token bill will thank\n  you.\n```\n\n", "url": "https://wpnews.pro/news/how-i-cut-45000-next-js-error-tokens-to-118-in-0-2ms-using-a-rust-mcp-server", "canonical_source": "https://dev.to/daffa2555/how-i-cut-45000-nextjs-error-tokens-to-118-in-02msusing-a-rust-mcp-server-1c7j", "published_at": "2026-09-15 03:19:09+00:00", "updated_at": "2026-09-15 04:01:10.886023+00:00", "lang": "en", "topics": ["ai-tools", "developer-tools", "ai-agents", "ai-safety", "mlops"], "entities": ["Tokenectomy Razor", "Model Context Protocol", "Next.js", "Rust", "Cursor", "Claude Desktop", "Cline", "Glama.ai"], "alternates": {"html": "https://wpnews.pro/news/how-i-cut-45000-next-js-error-tokens-to-118-in-0-2ms-using-a-rust-mcp-server", "markdown": "https://wpnews.pro/news/how-i-cut-45000-next-js-error-tokens-to-118-in-0-2ms-using-a-rust-mcp-server.md", "text": "https://wpnews.pro/news/how-i-cut-45000-next-js-error-tokens-to-118-in-0-2ms-using-a-rust-mcp-server.txt", "jsonld": "https://wpnews.pro/news/how-i-cut-45000-next-js-error-tokens-to-118-in-0-2ms-using-a-rust-mcp-server.jsonld"}}