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"Statistics of China's Population" matching MCP servers:

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    Enables exploratory data analysis through an MCP server, allowing AI assistants to load datasets, compute summary statistics, generate diagnostic plots, perform correlation analysis, and produce full markdown reports.
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    MIT
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    Enables reading and analysis of vector spatial data through Claude Desktop, supporting formats like FileGDB, Shapefile, GeoJSON, and GeoPackage with tools for layer listing, schema inspection, field statistics, feature extraction, and interactive map rendering.
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    4
    MIT
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    An MCP server for the Xe Currency Data API that brings live FX rates, historical analysis, and quant-flavored tools into AI tools, working out of the box with zero credentials via Frankfurter/ECB data.
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    MIT
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    MCP server for the ESRU-EMOVI 2023 social mobility survey in Mexico. Enables AI assistants to query weighted statistics, transition matrices, and explore variables from the survey using natural language.
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    MIT
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    An unofficial MCP server that provides 17 tools for Yandex/Google rank tracking via the Topvisor API v2, enabling project management, keyword import, asynchronous position checks, and retrieval of history and SERP snapshots.
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    MIT
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    A Python-based MCP server providing mathematical computation tools and plotting utilities for a wide range of math topics including calculus, matrix operations, statistics, and more.
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    MIT
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    A local Python MCP server for AI-assisted development of Yandex DataLens dashboards, enabling inspection, planning, validation, and guarded application of changes.
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    Apache 2.0
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    Exposes a broad mathematics toolkit including symbolic algebra, calculus, numerical methods, linear algebra, statistics, discrete math, graph theory, rendering, and optional GPU acceleration via MCP tools for use with Claude Desktop and other MCP hosts.
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    A Model Context Protocol server providing mathematical and scientific computing capabilities via NumPy, pandas, SciPy, and Matplotlib, with 19 tools for linear algebra, statistics, numerical methods, data processing, and plotting.
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    MIT
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    Enables conversational patent data analysis through a set of tools for trend analysis, clustering, word cloud generation, and more. Allows natural language queries to explore patent datasets with structured results and visualizations.
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    AGPL 3.0
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    A virtual statistician MCP server that provides real statistical methods—design of experiments, hypothesis testing, regression, SPC, MSA—via tested Python libraries, with plain-language interpretations and plotted outputs.
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    MIT