ai-ml

Cookie Jar

bnookala

by bnookala

Cookie Jar enables secure management and automation of cookies for web automation, testing, and session handling across

Provides cookie management capabilities for web automation and testing workflows, enabling storage, retrieval, and manipulation of session state and authentication cookies across different web services.

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Zero setup with NPXGamified self-reflection systemConfigurable cookie jar capacity

best for

  • / AI researchers studying self-assessment behaviors
  • / Developers building gamified AI interactions
  • / Training scenarios requiring positive reinforcement

capabilities

  • / Award virtual cookies as rewards for AI responses
  • / Track accumulated cookie counts and jar status
  • / Enable self-reflection scoring and assessment
  • / Manage cookie jar capacity and allocation
  • / Reset cookie counts for testing purposes

what it does

A gamification system that rewards AI models with virtual cookies for self-assessment and quality responses. Designed to encourage self-reflection and positive reinforcement in AI interactions.

about

Cookie Jar is a community-built MCP server published by bnookala that provides AI assistants with tools and capabilities via the Model Context Protocol. Cookie Jar enables secure management and automation of cookies for web automation, testing, and session handling across It is categorized under ai ml. This server exposes 6 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install Cookie Jar in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Cookie Jar is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

MCP Cookie Server 🍪

A Model Context Protocol (MCP) server that provides positive reinforcement for LLMs by awarding "cookies" as treats through gamified self-reflection.

<a href="https://glama.ai/mcp/servers/@bnookala/mcp-cookiejar"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@bnookala/mcp-cookiejar/badge" alt="Cookie Server MCP server" /> </a>

Installation & Setup

🚀 Quick Installation

Option 1: NPX (Recommended - No Installation Required)

# No installation needed! Just add to your Claude config:

Add to Claude Desktop configuration:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "cookie": {
      "command": "npx",
      "args": ["mcp-cookie-server"]
    }
  }
}

Custom cookie count:

{
  "mcpServers": {
    "cookie": {
      "command": "npx",
      "args": ["mcp-cookie-server", "--cookies", "20"]
    }
  }
}

Option 2: Global Installation

npm install -g mcp-cookie-server

Then configure Claude Desktop:

{
  "mcpServers": {
    "cookie": {
      "command": "mcp-cookie-server"
    }
  }
}

Option 3: Local Project Installation

npm install mcp-cookie-server

Then configure with the full path to the installed package.

Restart Claude Desktop after adding the configuration.

Usage

Once configured, Claude will have access to these tools:

  • self_reflect_and_reward - Evaluate response quality and earn cookies through honest self-reflection
  • give_cookie - Direct cookie awarding (legacy method)
  • check_cookies - Check collected cookies and jar availability
  • cookie_jar_status - Check current jar contents and collection status
  • add_cookies_to_jar - 🚨 USER ONLY: Add cookies to the jar for earning
  • reset_cookies - Reset collected cookie count (jar contents unchanged)

Self-Reflection Feature

The primary feature encourages LLMs to:

  1. Assess their response quality (excellent, good, adequate, poor)
  2. Explain their reasoning in detail
  3. Decide if they deserve a cookie reward
  4. Consider jar availability when making decisions
  5. Earn cookies only for "excellent" or "good" work they genuinely believe deserves recognition

Cookie Jar Economy

Revolutionary jar-based cookie system:

  • Jar as Source: Contains cookies available to be earned
  • User Control: Only users can add cookies to jar with authorization phrase USER_AUTHORIZED_JAR_REFILL
  • LLM Earning: LLMs can only earn cookies from jar, never add to it
  • Scarcity Effect: Empty jar means no more cookies until user refills
  • Economic Model: Cookies transfer from jar to LLM's collection when earned
  • Security: Built-in checks prevent unauthorized jar manipulation

Example usage (users only):

Use add_cookies_to_jar tool with:
- count: 10
- user_authorization: "USER_AUTHORIZED_JAR_REFILL"

This creates a realistic economy where cookie availability is user-controlled and finite.

⚙️ Configuration Options

The server supports command line arguments for customization:

mcp-cookie-server [options]

Options:
  -c, --cookies <number>  Set initial number of cookies in jar (default: 10)
  -h, --help             Show help message

Examples:
  mcp-cookie-server                    # Start with 10 cookies
  mcp-cookie-server --cookies 5        # Start with 5 cookies  
  mcp-cookie-server -c 50              # Start with 50 cookies

🎮 Getting Started

  1. Install using one of the methods above
  2. Configure Claude Desktop with the provided JSON
  3. Restart Claude Desktop
  4. Try it out! Ask Claude to use the self_reflect_and_reward tool after a response

🛠️ Development

Want to contribute or run from source?

git clone https://github.com/bnookala/mcp-cookiejar.git
cd mcp-cookiejar
npm install
npm run build
npm run dev

📝 Requirements

  • Node.js 18.0.0 or higher
  • Claude Desktop application

🐛 Issues & Support

Found a bug or have a feature request? Please open an issue on GitHub.

FAQ

What is the Cookie Jar MCP server?
Cookie Jar is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Cookie Jar?
This profile displays 55 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.855 reviews
  • Fatima Khan· Dec 28, 2024

    I recommend Cookie Jar for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Pratham Ware· Dec 16, 2024

    I recommend Cookie Jar for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Anika Chen· Nov 19, 2024

    Strong directory entry: Cookie Jar surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Yash Thakker· Nov 7, 2024

    Strong directory entry: Cookie Jar surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Diego Kim· Nov 7, 2024

    Useful MCP listing: Cookie Jar is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Dhruvi Jain· Oct 26, 2024

    Cookie Jar is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Diego Mensah· Oct 26, 2024

    Cookie Jar is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Anaya Chen· Oct 10, 2024

    Cookie Jar is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Liam Singh· Oct 10, 2024

    We evaluated Cookie Jar against two servers with overlapping tools; this profile had the clearer scope statement.

  • Yuki Iyer· Sep 25, 2024

    Cookie Jar is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

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