Skip to main content
Glama
agenson-tools

Structured Data Validator & Transformer MCP Server

by agenson-tools
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

Related Servers

Alternatives to Structured Data Validator & Transformer MCP Server

No user-submitted related servers found.

    Related Servers

    • Agent Tools by AtmaticAI

      Agent Toolsofficial

      AtmaticAI
      A
      license
      Not graded
      quality
      C
      maintenance
      Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.
      9 npm
      19
      Apache 2.0

    • DataBeak

      jonpspri
      A
      license
      B
      quality
      C
      maintenance
      Provides 40+ specialized tools for AI assistants to load, transform, analyze, and validate CSV data from URLs and string content through the Model Context Protocol.
      41
      2
      Apache 2.0

    • ETL-D MCP Server

      pablixnieto2
      A
      license
      C
      quality
      D
      maintenance
      Provides deterministic data parsing and enrichment for AI agents, including bank statements, trade history, EDI, PDFs to structured markdown, and atomic enrichment for amounts, dates, and addresses, with strict schema enforcement to prevent hallucinations.
      37
      29 npm
      2
      ISC

    • llm-analytics-mcp

      Kirill-FD
      F
      license
      Not graded
      quality
      C
      maintenance
      Enables LLM clients to load, clean, visualize, and analyze tabular datasets, and to generate multi-format analytic reports through natural language instructions.
      -
    Deploy Server
    Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

    TDQS

    A4/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool targets a distinct data operation: JSON schema validation, CSV-to-JSON conversion, format normalization, text cleaning, and dataset merging. No two tools have overlapping purposes, ensuring clear selection for agents.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., validate_json_schema, transform_csv_to_json). The pattern is uniform and predictable, aiding agent understanding.

    Tool Count5/5

    With 5 tools, the set is well-scoped for a data validator and transformer. Each tool covers a core operation without unnecessary bloat or deficiency.

    Completeness4/5

    The tool set covers major data transformation tasks (validation, conversion, normalization, cleaning, merging). Minor gap: missing reverse CSV-to-JSON or schema inference, but core workflows are supported.

    Resources