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"Querying Elasticsearch (ES)" matching MCP servers:

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    17 decision intelligence algorithms as MCP tools for AI agents. Bandits (UCB1, Thompson), LP/MIP solver (HiGHS), Monte Carlo simulation, Bayesian inference, graph analytics (PageRank, Louvain), genetic algorithms, CMA-ES, anomaly detection, time series forecasting, and more. All under 25ms, deterministic, zero LLM cost.
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    MIT
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    Bilingual (EN/ES) AI-writing detection that shows the evidence instead of a percentage: named tells with line and column, hidden-character inspection, and citation cross-checking against a document's own bibliography. Seven of its nine tools run entirely locally and never touch the network.
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    MIT
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    Enables natural language querying of oceanographic data from the NES-LTER API, including CTD profiles, cruise datasets, and station information.
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    Access Global Fishing Watch data from any MCP-compatible AI assistant or terminal: search vessels, retrieve fishing activity and port events, look up marine regions, and compute aggregate statistics.
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    Apache 2.0
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    Enables natural language querying and management of Apache Superset dashboard metadata, including user activity, data lineage, and change tracking.
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    MIT
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    Enables querying Korean and US stock information, quotes, account assets, and order history via Toss Securities Open API. Optionally supports order placement with preview and confirmation safeguards.
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    MIT
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    Enables querying and retrieving bacterial and viral genomic data, features, antimicrobial resistance, and epitopes from the BV-BRC API using natural language.
    MIT
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    Enables querying HEC-RAS project information, geometry elements, plan results, and compute messages through natural language, allowing interaction with hydraulic modeling projects.
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    MIT
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    Provides structured access to Nepal Stock Exchange market data through the Model Context Protocol, enabling AI integration for querying real-time stock data and market analysis.
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    MIT
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    Enables querying economic statistics from over 80 providers via DBnomics, with tools to list providers and datasets.
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    MIT
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    Enables AI agents to interact with the Titanic passenger database via MCP, providing tools for querying, analysis, and exploration.
    MIT