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668,430 tools. Updated 2026-10-17 05:40

"Understanding and Using JSON" matching MCP tools:

  • List all files and directories in a specified path, with [FILE] and [DIR] prefixes to distinguish items, enabling quick understanding of directory structure.
    -
  • Run a live operation on a connected provider using your project's first enabled connection. Pass inputs as key=value pairs or JSON; calls may incur provider charges and return JSON.
    MIT
  • Extract text from local image files using OCR. Converts image-based content into structured JSON and a text summary for downstream processing.
    MIT
  • Convert PDFs and scanned images into JSON representation, preserving text, fonts, images, vectors, and formatting.
    MIT

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  • Repairs truncated or malformed LLM JSON outputs (trailing commas, markdown fences, unquoted keys).

  • https JSON URL to tidy markdown. x402 $0.005 USDC, Base. As is, no warranty.

  • Analyze images using Gemini's multimodal understanding. Provide one or more images and a prompt to receive a text-based analysis of their content.
    Apache 2.0
  • Retrieve recent file system changes from watched directories to track file creations, modifications, deletions, and moves for understanding recent work.
    MIT
  • Retrieve random document samples from MongoDB collections for data exploration, testing, and analysis in JSON or CSV formats.
    MIT
  • Analyze code files to identify top-level symbols and their structure, providing a quick overview for understanding new codebases or files.
    GPL 3.0
  • Filter JSON data from files or URLs using shape objects to extract specific fields and nested structures, reducing data volume for focused analysis.
    MIT
  • Analyze JSON data size by field using a shape object to identify storage usage patterns and optimize data structure efficiency.
    MIT
  • List Oracle Cloud Infrastructure AI/ML services including Generative AI, Vision, Speech, Language, and Document Understanding. Filter by service type or model.
    Apache 2.0
  • Analyze data patterns and relationships around specific coordinates for validation, error investigation, and contextual understanding in CSV datasets.
    Apache 2.0
  • Find code by meaning using semantic search with natural language queries. Combines AI understanding with text matching to locate relevant snippets, handling typos and variations.
    MIT
  • List all privileges granted on tables, views, sequences, and functions in a PostgreSQL schema. Useful for security audits and understanding who has access to what.
    MIT
  • Search datasets using semantic understanding with synonym expansion and Serbian-English translation. Suggests related datasets when no exact match is found.
    MIT