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Credit Optimizer V5

rafsilva85/credit-optimizer-v5 · 51 stars · Python · MIT

MCP server AI-powered credit optimization for Manus AI. Automatically analyzes each prompt and routes to the cheapest capable model (Standard vs Max, Agent vs Chat mode). Saves 30-75% on Manus credits with zero quality loss. Tested across 53 real-world scenarios. Free and open-source.

Install

The repo has no one-line install. Follow its README.

Published as

  • PyPImcp-credit-optimizerstdio

From the server's entry in the official MCP Registry.

Open the repo

Files

README.md

PyPI Version Downloads License: MIT Manus AI Stars Quality Loss Scenarios Sales

Manus Power Stack

47% of your Manus credits are being wasted. This fixes it automatically.

Zero downsides. 47% average savings. Pays for itself in ~36 prompts. Audited across 53 adversarial scenarios. Quality Veto Rule: if it can't save without loss, it doesn't touch your task.

Get it: Landing Page · Gumroad ($12) · Power Bundle ($12) · SkillFlow Free MCP Server: PyPI · Smithery

As Seen On

Dev.to · PulseMCP · Smithery · MCPServers.org · Agensi.io · Indie Hackers · Awesome Manus AI


Why Your Credits Disappear

Manus charges credits per task. Most users waste 30–75% because of four default behaviors:

Problem What Happens Waste
Wrong model routing Simple tasks run in Max mode when Standard produces identical results Up to 5x overpay
Slow browser navigation Each page takes 8–45 seconds via browser tool calls, burning credits on wait time 150+ seconds per 10 URLs
No chat detection Tasks that cost $0 in Chat Mode (Q&A, brainstorm, translation) run in Agent Mode 100% overpay
Context bloat Tokens accumulate across steps — each subsequent step costs more than the last Exponential growth

These aren't bugs. They're default settings. The Power Stack overrides all four.


Zero Downsides

This is the most important thing to understand:

The Power Stack can never make things worse. It has a hardcoded Quality Veto Rule: if an optimization would reduce output quality by even 1%, it skips that optimization entirely. In the worst case, it does nothing. In the best case, it saves you 75%.

There is no scenario where installing the Power Stack produces a worse result than not having it.


What's Inside

Credit Optimizer v5 — Smart Routing

Analyzes every prompt before execution and decides the cheapest path that delivers identical quality.

  • Intent Classification across 12 categories (code, research, creative, data, translation...)
  • Model Routing: Standard vs Max — only uses Max when complexity genuinely requires it
  • Chat Mode Detection: Routes simple Q&A to Chat Mode ($0 cost)
  • Batch Detection: Groups related tasks to reduce overhead
  • Context Hygiene: Compresses accumulated context to keep token costs linear

Fast Navigation v2.0 — Raw Speed

Replaces slow browser tool calls with a programmatic toolkit.

  • httpx + selectolax replaces Playwright overhead (30–2,000x faster)
  • Browser Cookie Bridge for authenticated sites
  • Async parallel fetching — 10 URLs in 1.3 seconds instead of 150+ seconds
  • Intelligent disk caching with TTL — repeated visits are instant

Together: The Compound Effect

Credit Optimizer decides what to optimize. Fast Navigation decides how fast to execute it. Together, they multiply:

Metric Without Stack With Stack Improvement
Simple Q&A cost Full price $0 (Chat Mode) 100% saved
10-URL research 150+ seconds 1.3 seconds 115x faster
Web scraping task Full credits 33% of original 67% saved
Full-stack web app Full credits 40% of original 60% saved
Research report 12 minutes 2 minutes 6x faster
Average across all tasks Baseline 47% less 47% saved

The Math: Payback in ~36 prompts

The Power Stack costs $9 one-time (or $12 for the bundle with Fast Navigation). Here's how fast it pays for itself:

Plan Monthly Cost 47% Wasted Daily Waste Payback
Plus ($39/mo) 6,500 cr/day ~3,055 cr/day ~$0.44/day ~20 prompts
Max ($99/mo) 16,250 cr/day ~7,637 cr/day ~$0.92/day ~10 prompts
Teams ($79/user/mo) Varies ~47% Varies 1–2 days

After payback, every prompt saves you money. For the rest of your Manus subscription. Forever.

Annual savings estimate: ~$500–$1,000+ depending on usage.


Installation

As Manus Skill (recommended — $9 individual / $12 bundle)

  1. Purchase from Gumroad or SkillFlow
  2. Copy skill files to ~/skills/credit-optimizer/ and ~/skills/fast-navigation/
  3. Both activate automatically on every task — no configuration needed

As MCP Server (free — Credit Optimizer only)

pip install mcp-credit-optimizer
python -m mcp_credit_optimizer

Add to your MCP config:

{
  "mcpServers": {
    "credit-optimizer": {
      "command": "python",
      "args": ["-m", "mcp_credit_optimizer"]
    }
  }
}

Works with Claude Desktop, Cursor, Windsurf, Copilot, and any MCP-compatible client.

Why pay when the MCP server is free? The MCP server saves credits when you remember to call it. The Manus Skill saves credits on every single prompt automatically — no manual invocation needed. The Skill also includes Fast Navigation (115x speed boost), which is not available as MCP.


Audit Results

All 53 test scenarios pass with zero quality degradation:

Category Scenarios Quality Loss
Code generation (Python, JS, React, SQL) 12 0%
Creative writing (blog, marketing) 8 0%
Data analysis (CSV, JSON, API) 7 0%
Research (multi-source synthesis) 6 0%
Translation & localization 5 0%
Bug fixing & debugging 5 0%
Documentation generation 5 0%
Mixed-intent tasks 5 0%

What Users Say

"Everyone hates the Manus credit-based system. It's insane how fast credits burn." — Reddit, 90 upvotes

"I used 100,000 credits in a week and a half. That's my entire monthly allocation gone." — Reddit

"Manus is so expensive it's absurd. $200/month and credits still run out." — Reddit

The Power Stack exists because these frustrations are real — and fixable.


Resources


Links

Channel URL
Landing Page creditopt.ai
Buy Individual ($9) Gumroad
Buy Bundle ($12) Gumroad
SkillFlow skillflow.builders
PyPI (Free MCP) pypi.org
Smithery smithery.ai
PulseMCP pulsemcp.com
Awesome List github.com/rafsilva85/awesome-manus-ai

License

MIT — see LICENSE for details.

Built by Rafael Silva · creditopt.ai

Facts

Kind
MCP server
Repo
rafsilva85/credit-optimizer-v5
Group
Uncategorized
Stars
51
License
MIT
Language
Python
Last push
2026-05-25
Forks
12
MCP Registry
io.github.rafsilva85/credit-optimizer
Homepage
creditopt.ai
Topics
ai-agents, cost-optimization, mcp-server, manus-ai, manus-skill, mcp, ai-tools, credit-optimizer, python

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