MCP server that reduces LLM context by removing code comments and converting data formats to TOON
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
💡 Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
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.
The toon-parse-mcp MCP server helps AI agents (like Cursor, Claude Desktop, etc.) operate more efficiently by:
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).protocol://mandatory-efficiency: Provides a strict system instruction prompt for LLMs to ensure they use the optimization tools correctly.toon-parse-mcpcommandpython3 -m toon_parse_mcp.server (Ensure your environment is active or use absolute path to python)~/.codeium/windsurf/mcp_config.json directly.mcpServers object:~/.gemini/antigravity/mcp_config.json directly.mcpServers object:Add this to your claude_desktop_config.json:
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".
To run the test suite:
mcp >= 1.25.0toon-parse >= 2.4.3MIT License - see LICENSE for details.
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