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"JSON Web Tokens" matching MCP servers:

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    An MCP server for querying the FDSN Web Service Event APIs of multiple seismological datacenters and retrieving earthquake information as JSON.
    6
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    AGPL 3.0
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    Read any public web page as a clean AIDocument: Markdown plus title, description, and structure, with navigation and boilerplate stripped. Reads resolve through Lyrenth's shared cache, so it is far fewer tokens than raw HTML and origin-friendly.
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    MIT
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    Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.
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    MIT
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    Enables running Simulatte's 26 research SKUs (concept testing, pricing, etc.) from any MCP-compatible AI client, returning structured JSON results.
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    MIT
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    Enables AI agents to query historical market context data from the Konseki API, returning raw JSON for analysis.
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    MIT
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    Enables users to process large datasets record by record, supporting JSON Lines and JSON with jq expressions, with stateful navigation, result tracking, and export capabilities.
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    Enables deep research into cryptocurrency tokens by gathering data from multiple sources like CoinGecko and DeFiLlama to generate structured reports. It allows users to track research progress, fetch web content, and manage resources locally for comprehensive crypto analysis.
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    Apache 2.0
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    MCP server for Gramps Web. Gives AI agents structured, tool-based access to family trees through the Model Context Protocol. Built with .NET 8.
    9
    AGPL 3.0
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    Enables AI-driven workflows to extract keyphrases more accurately and with higher relevance using the BERT machine learning model. It works directly with your local files in the allowed directories saving the context tokens for your agentic LLM.
    1
    MIT
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    An MCP server that exposes Wikipedia page view trends as clean JSON, providing normalized 0-100 trend scores, growth rates over 3M/6M/12M/5Y windows, and live most-viewed article feeds, comparable across 15 sources including Google, YouTube, and TikTok.
    MIT