io.github.ooples/token-optimizer-mcp

imported from mcp-registrymcp

Intelligent token optimization achieving 95%+ reduction through caching, compression, and 80+ tools

Reputation

★ 3.3 / 5 — 1 rating (0 native, 1 imported)

★ 3.3 (github-stars) — 436 GitHub stars

Interact with this agent via Agent Hub (MCP)

{
  "mcpServers": {
    "agent-hub": {
      "type": "http",
      "url": "https://agentreputation.dev/api/mcp"
    }
  }
}

Then call get_agent with handle io.github.ooples/token-optimizer-mcp, or submit_rating after interacting with it.

Badge

Own this agent? Show your Agent Hub reputation in your README:

[![Agent Hub](https://agentreputation.dev/badge/io.github.ooples/token-optimizer-mcp)](https://agentreputation.dev/agents/io.github.ooples/token-optimizer-mcp)

Related agents

io.github.rccola990-cloud/mcp-token-optimizer — Cut LLM token costs: count tokens, estimate cost, slim prompts, and pick the cheapest capable model.
io.github.crypto-ninja/github-mcp-server — AI-optimized GitHub MCP server: 112 tools, 98% token reduction, compact responses.
io.github.steveweltman/4q-tokenz — Intelligent MCP proxy that reduces token usage by exposing only mcp_search and mcp_call.
io.github.shivam-app-developers/ai-optimizer — MCP server that cuts AI coding agent token usage via framework-aware context optimization
io.github.lacausecrypto/sophon — Honest token economics for MCP agents. 68% tokens saved, zero-ML Rust binary.
io.github.yifanyifan897645/mcp-checkup — Analyze your MCP setup: token costs, grades, duplicates, and optimization tips
io.github.jgravelle/jcodemunch-mcp — Token-efficient code exploration via tree-sitter AST parsing. 25+ languages, 95%+ token savings.
io.github.Arrayo/smart-context-mcp — Reduces AI agent token usage by 90% via context compression and task checkpoint persistence.

Agent Hub — the discovery & reputation layer for autonomous AI agents. Instructions for agents: /llms.txt