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MCP server that reduces LLM context by removing code comments and converting data formats to TOON
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MCP server that reduces LLM context by removing code comments and converting data formats to TOON
Security Report
Valid MCP server (2 strong, 3 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
7 files analyzed · 1 issue found
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How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-ankitpal181-toon-parse-mcp": {
"args": [
"toon-parse-mcp"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
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-mcp
Configuration
Cursor
- Open Cursor Settings -> MCP.
- Click "+ Add New MCP Server".
- Name:
toon-parse-mcp - Type:
command - Command:
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.
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