"Understanding and Using JSON" matching MCP servers:

A minimal MCP server that exposes Gemini's web and multimodal understanding (video, audio, document, image) through five dedicated tools.

Local MCP tool for understanding JSON Schema files while planning tests, summarizing types, required fields, constraints, and generating placeholder paths without copying data.

Enables local video inspection and offline transcription with timestamped JSON and Markdown output, enforced filesystem boundaries, and reproducible content-addressed caching.

An MCP server that converts raw text prompts into structured JSON prompts using heuristic keyword extraction — no API keys required.

A powerful MCP server for querying and processing large Swagger/OpenAPI JSON documents, enabling LLMs to efficiently access API documentation without loading entire files.

JSON Contracts is a local MCP server for transforming natural language into Git-controlled JSON contracts, JSON Schema validation, and structured LLM/agent outputs.

Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.

A Model Context Protocol server for querying large JSON files using JSONPath expressions, enabling LLMs to efficiently search and extract information from large JSON data.

Enables efficient JSON file editing with targeted read, write, delete, and deep merge operations using dot notation paths, optimized for managing multilingual projects and large configuration files.

A Model Context Protocol (MCP) server based on OpenRPC, providing JSON-RPC function invocation and method discovery services.

MCP server for sealing and opening JSON with φ-split keyword shares and benefit checks.

Enables LLMs to query and manipulate JSON data from URLs using JSONPath expressions with array, string, numeric, date, and aggregation operations via standardized tools.

Enables compression and decompression of JSON data using the token-optimized ASON format, reducing token usage by 20-60% for LLM applications.

Lets agents and CLI users inspect the shape of large JSON and JSONL files and extract exactly the values they need using jq-like expressions, returning compact bounded results instead of flooding context.

MCP App that renders a json-render spec from the model as real Angular Material components inline in the chat (Claude, ChatGPT, VS Code, Cursor). One tool, render-ui, over a 29-component catalog; the UI renders while the model is still writing.

Provides tools to validate, format, and query JSON strings via MCP. Enables AI agents to work with JSON data without needing keys or internet.

An MCP server that provides tools for JSON validation, diffing, and transformation operations such as flattening and renaming. It also enables data format conversion between JSON, CSV, and YAML to streamline data processing for AI agents.

MCP server for validating JSON against JSON Schema and repairing malformed/invalid JSON.

Enables AI agents to convert CSV text into JSON arrays with automatic delimiter detection and optional header-row handling, accessed through a pay-per-call x402 micropayment API.

Validates JSON syntax and optionally checks against a JSON Schema, with pay-per-call via x402 micropayments.