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JSON to TOON MCP Server

by mhabedini
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JavaScript
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Alternatives to JSON to TOON MCP Server

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    Related Servers

    • TOON MCP Server

      HasnainAli47
      A
      license
      Not graded
      quality
      D
      maintenance
      Converts JSON data and system prompts to and from TOON (Token-Oriented Object Notation) format, reducing token usage by 30-60% when interacting with LLMs while preserving data structure.
      MIT

    • TOON MCP Server

      elminson
      A
      license
      A
      quality
      D
      maintenance
      Enables users to convert structured data into Token-Oriented Object Notation (TOON) to reduce LLM token usage and costs by up to 70%. It provides tools for encoding, decoding, and analyzing data formats like JSON, CSV, and XML to optimize prompt efficiency.
      4
      5 npm
      3
      MIT

    • TOONer

      chaindead
      A
      license
      Not graded
      quality
      C
      maintenance
      MCP proxy that wraps any MCP server and transparently converts JSON responses in tools/call to TOON format — a token-efficient alternative to JSON optimized for LLMs (~40% fewer tokens).
      22
      MIT

    • JSON2TOON MCP Server

      muhammedehab35
      A
      license
      B
      quality
      D
      maintenance
      Advanced Token-Optimized Object Notation MCP server that compresses JSON with up to 85% token reduction using AI-powered pattern detection, providing lossless compression and decompression through 12 MCP tools.
      12
      9
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.5/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: analyze_token_savings is for analysis, convert_json_to_toon is for one-way conversion, and convert_toon_to_json is for reverse conversion. There is no overlap or ambiguity between these functions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (analyze_token_savings, convert_json_to_toon, convert_toon_to_json) with clear, descriptive terms. There are no deviations in naming style.

    Tool Count4/5

    Three tools are well-scoped for a JSON/TOON conversion server, covering analysis and bidirectional conversion. It feels slightly minimal but reasonable, as core operations are present without bloat.

    Completeness5/5

    The tool set provides complete coverage for the domain: analysis of token savings, conversion from JSON to TOON, and conversion back from TOON to JSON. There are no obvious gaps for the stated purpose of efficient LLM token usage.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources