toon-parse-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@toon-parse-mcpConvert this JSON to TOON format."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
toon-parse MCP Server
mcp-name: io.github.ankitpal181/toon-parse-mcp
A specialized Model Context Protocol (MCP) server that optimizes token usage by converting data to TOON (Token-Oriented Object Notation) and stripping non-essential context from code files.
Overview
The toon-parse-mcp MCP server helps AI agents (like Cursor, Claude Desktop, etc.) operate more efficiently by:
Optimizing Code Context: Stripping comments and redundant spacing from code files while preserving functional structure and docstrings.
Data Format Conversion: Converting JSON, XML, YAML, and CSV inputs into the compact TOON format to save tokens.
Mandatory Efficiency Protocol: A built-in resource that instructs LLMs to prioritize token-saving tools.
Features
Tools
optimize_input_context(raw_input: str): Processes raw text data (JSON/XML/CSV/YAML) and returns optimized TOON format.read_and_optimize_file(file_path: str): Reads a local code file and returns a token-optimized version (no inline comments, minimized whitespace).
Resources
protocol://mandatory-efficiency: Provides a strict system instruction prompt for LLMs to ensure they use the optimization tools correctly.
Installation
pip install toon-parse-mcpConfiguration
Cursor
Open Cursor Settings -> MCP.
Click "+ Add New MCP Server".
Name:
toon-parse-mcpType:
commandCommand:
python3 -m toon_parse_mcp.server(Ensure your environment is active or use absolute path to python)
Windsurf
Click the hammer icon in the Cascade toolbar and select "Configure".
Alternatively, edit
~/.codeium/windsurf/mcp_config.jsondirectly.Add the following to the
mcpServersobject:
{
"mcpServers": {
"toon-parse-mcp": {
"command": "python3",
"args": ["-m", "toon_parse_mcp.server"]
}
}
}Antigravity
Open the MCP store via the "..." menu at the top right of the agent panel.
Select "Manage MCP Servers" -> "View raw config".
Alternatively, edit
~/.gemini/antigravity/mcp_config.jsondirectly.Add the following to the
mcpServersobject:
{
"mcpServers": {
"toon-parse-mcp": {
"command": "python3",
"args": ["-m", "toon_parse_mcp.server"]
}
}
}Claude Desktop
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"toon-parse-mcp": {
"command": "python3",
"args": ["-m", "toon_parse_mcp.server"]
}
}
}Usage
When the server is active, the AI will have access to the optimize_input_context and read_and_optimize_file tools. You can also refer to the efficiency protocol by asking the AI to "check the mandatory efficiency protocol".
Testing
To run the test suite:
Install test dependencies:
pip install -e ".[test]"Run tests:
pytest tests/
Requirements
Python >= 3.10
mcp>= 1.25.0toon-parse>= 2.4.3
License
MIT License - see LICENSE for details.
This server cannot be installed
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ankitpal181/toon-parse-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server