AI Token Optimizer

AI Token Optimizer

An MCP server that cuts AI coding-agent token usage by 60–80% via framework-aware context optimization.

Category
Visit Server

README

AI Token Optimizer

An MCP server that cuts AI coding-agent token usage by 60–80% via framework-aware context optimization.

CI CodeQL npm License: MIT

<!-- mcp-name: io.github.shivam-app-developers/ai-optimizer -->

AI coding agents read whole files when they need 15 lines. They load *.g.dart, R.java, node_modules/, and dist/ into context — then do it again next turn. AI Token Optimizer is a Model Context Protocol server that intercepts those tool calls and strips framework noise before it reaches the model.

Works with anything that speaks MCP: Claude Code, Cursor, Cline, Continue, Zed, JetBrains AI, GitHub Copilot agent mode, Antigravity, Windsurf, OpenAI Codex CLI.

Quickstart

npm install -g @ai-optimizer/core

Then point your agent at the ai-optimizer stdio server. For Claude Code, add to ~/.claude/settings.json:

{
  "mcpServers": {
    "ai-optimizer": {
      "command": "ai-optimizer"
    }
  }
}

Or scaffold the config and preview your savings automatically:

npx @ai-optimizer/init
# "we'd skip 47 files, ~14K tokens/session, ~$0.42/session at Sonnet pricing"

Full per-agent setup (Cursor, others), LSP install, and verification steps live in packages/core/README.md.

What it does

It registers tools the agent uses instead of its built-in file/dir/error reads:

Tool What it saves
optimized_read_file Framework-aware skip + optional line slice
optimized_list_files Walks the tree applying ignore globs (+ .gitignore)
optimized_grep Content search scoped by ignore filters
optimized_diagnostics Spawns the right LSP, returns errors + a narrow code window
read_symbol LSP workspace/symbol slice instead of a full-file read (Pro/LSP)
strip_bash_noise Strips ANSI, npm/maven/gradle progress, JVM warnings
optimizer_status Detected frameworks, active packs, cumulative tokens saved

When a project type is detected (e.g. Python via pyproject.toml), the matching pack's ignore rules activate automatically. .gitignore is respected on top.

Tiers

Free (MIT core) Pro ($9/mo) Team ($29/seat)
Framework packs Python, JS/TS + React, Flutter, Java, Kotlin, Go, Rust, C#, Swift, Ruby, Elixir, PHP, Solidity all Pro packs
History compaction — ✓ ✓
Scheduler (claude -p cron) — ✓ + work-stealing across providers
Audit log + secret redaction + policy — — ✓

See PRICING.md. Behavior-changing or data-sharing features (scheduler, work-stealing, telemetry) are off by default and require explicit opt-in. Display-only features (dollar-value savings) default on.

Monorepo layout

Package Purpose Published
packages/core MCP server + free packs npm (MIT)
packages/init npx @ai-optimizer/init config + savings preview npm
packages/sdk definePack plugin SDK npm
packages/context-mode-import Import .contextmode configs npm
packages/pro Pro/Team packs + scheduler + audit private
apps/landing, apps/dashboard, apps/vscode-extension, apps/license-server Site, local dashboard, IDE widget, license issuance private
tools/pack-bench Pack quality benchmark harness private

Architecture details: ARCHITECTURE.md.

Development

npm install            # at repo root (workspaces)
npm run build          # build all packages
npm test               # run all test suites

Security

Local-only by design — license validation is the only network call. Report vulnerabilities per SECURITY.md.

License

Core engine is MIT — see LICENSE. Pro/Team packs are proprietary.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured