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"How to scrape data from websites into JSON" matching MCP servers:

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    JSON Contracts is a local MCP server for transforming natural language into Git-controlled JSON contracts, JSON Schema validation, and structured LLM/agent outputs.
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    Apache 2.0
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    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.
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    A comprehensive web scraping server that transforms web content into clean, agent-ready Markdown with automatic citations and efficient caching. It features a robust suite of tools for metadata extraction, sentiment analysis, SEO auditing, and security scanning while strictly adhering to robots.txt policies.
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    MIT
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    An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.
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    Apache 2.0
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    Provides tools to validate, format, and query JSON strings via MCP. Enables AI agents to work with JSON data without needing keys or internet.
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    MIT
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    Provides deterministic conversion between YAML and JSON formats, enabling autonomous agents to flawlessly translate complex configurations without LLM formatting errors.
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    Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.
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    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.
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    MIT
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    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.
    40
    MIT
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    Enables repair of malformed JSON strings into valid JSON for agent workflows by fixing common LLM formatting issues. Supports cleanup of code fences, smart quotes, unquoted keys, trailing commas, and missing brackets to ensure reliable data parsing.
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    Enables efficient navigation and search of large JSON files (>10MB) through intelligent path exploration and fuzzy search capabilities, designed to save tokens by avoiding loading entire files into context.
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    Provides read-only MCP tools to query the ETIM classification model, enabling AI agents to search classes, retrieve feature/unit definitions, and look up ETIM codes.
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    MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.
    11
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    Apache 2.0