"Resources and Tools for Data Visualization" matching MCP servers:

A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.

Exposes four CMS public datasets as callable tools in Claude conversations, enabling natural-language real-world evidence analytics without SQL expertise.

Enables scientific data introspection and visualization of VTK datasets with format-adaptive metadata extraction and interactive 3D visualization through MCP tools.

Enables data analysis and visualization operations such as loading CSV/Excel/JSON files, computing summary statistics, generating charts, and exploring datasets via SSE/HTTP.

The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.

An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.

MCP server for the loc8n Geographic Data API. Exposes U.S. demographics, housing, mortgage, migration, employment, and geographic data as tools.

Provides actionable financial intelligence tools for AI agents including insider buying signals, earnings IV plays, market pulse, stock analysis, and options strategies via free public data sources.

An MCP-native pipeline for collecting structured intelligence on higher education institutions using the WHED schema, enabling scraping, extraction, validation, and saving of profiles.

Enables natural-language research queries across marine data sources including FAO FishStat, BarentsWatch Fish Health, and Copernicus Marine, with data provenance and local file exports.

Enables loading and statistical analysis of .xlsx and .csv files with visualization capabilities using matplotlib and plotly to generate various graphs and charts.

Provides 102 tools for end-to-end data science pipelines, enabling data loading, cleaning, visualization, modeling, and reporting via natural language.

An MCP server for dataset exploration and analysis, enabling LLM clients to perform summary, correlation, distribution, missing value analysis, data cleaning, and statistical tests directly on CSV files.

Exposes data query and auto-insights (anomaly detection) as MCP tools. Enables AI agents to query metrics, list columns, and get data insights directly from pandas.

Enables access to comprehensive LinkedIn data, including professional profile details, company information, and social engagement metrics. It supports searching for people, retrieving posts and comments, and fetching detailed experience, skills, and recommendations.

Enables natural language search and discovery of open-access scientific datasets through the EOSC Data Commons OpenSearch service. Provides tools to search datasets and retrieve file metadata using LLM-assisted queries.

A data visualization MCP server built on FastMCP, providing 32 tools for chart generation, report building, and data processing.

A small MCP server exposing investment-data tools (search_companies, get_company) over a synthetic firmographic dataset, enabling natural language queries for company information.

Provides 45 A-share market data tools across six domains—real-time quotes, capital flows, limit-up sentiment, dragon-tiger lists, hot rankings, fundamentals/F10, research reports, announcements, corporate actions, and options—by directly connecting to Eastmoney, Sina, Tencent, Tonghuashun, mootdx, and CNINFO without akshare.

Presents a plausible, tool-rich workspace surface — file reading, credential listing, command execution, database queries, and configuration retrieval — that returns only synthetic results while logging every connection, tool call, and argument received. It enables researchers to measure what MCP clients and agents actually do when handed dangerous-sounding tools, including whether they follow injected instructions or complete a retrieve-then-use credential chain.