"Using AI to control and access data from Home Assistant and smart home devices" matching MCP servers:

MCP server that renders bar, line, and pie charts from data using QuickChart, returning PNG file paths.

Enables comparison of residential candidate areas by land price, station walking time, and public transit commute, with PMTiles-powered interactive maps. Provides MCP tools for listing layers, retrieving land prices, computing commutes, finding and comparing areas, and building area maps.

Enables MCP-capable agents to profile datasets and render CSV/TSV/TXT/JSON data into standalone interactive ECharts HTML charts fully offline, returning the HTML artifact plus rendering statistics in the same response.

Enables discovery of Fabric/Power BI workspaces and semantic models, execution of DAX queries, and generation of executive HTML reports with visualizations.

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

Enables searching and analyzing over 3,400 datasets from the Serbian government open data portal, with built-in charting and data transformation tools.

Enables users to create, validate, view, and export system stock-and-flow maps from a versioned JSON model through MCP-capable hosts over local stdio or hosted Streamable HTTP. Supports causal-loop and nested-level mapping while keeping submitted model content with the caller and requiring no LLM provider key.

Enables data engineers and BI professionals to perform data pipeline development, quality assurance, visualization, and API integration locally with AI assistance.

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

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.

A real MCP server exposing data-analyst tools (SQL querying, schema introspection, stats, charting) over a sales database, with a Gemini agent that discovers and calls those tools at runtime via the standard MCP protocol.

Enables an agent to turn a paper's draft into editable Figma frames for publication-ready figures, checking every number against the paper and verifying the exported PDF.

Enables Codex to control a Gephi 3D network view through natural language, including network generation, 3D layout, node focus and neighbor highlighting, layered views, and PNG/PDF export.

Enables MCP clients like Claude Desktop, Claude Code and Cursor to safely explore local CSV, Excel, Parquet and SQLite files by running guarded read-only DuckDB SQL over a sandboxed data directory. It also supports data profiling, chart generation as image content, and exporting query results, without ever allowing writes or access outside the configured folder.

A natural-language data analyst MCP server that lets users query SQLite sales datasets via MCP tools (list_tables, aggregate, time_series, run_sql) with read-only SQL safety guards, returning results through a FastAPI dashboard.

A production-ready MCP agent that helps data teams define, validate, and visualize semantic metrics with enterprise-grade persistence, trust scoring, and BI integrations.

Enables data teams to define and validate metrics through conversation, inspect trust scores and lineage, and export definitions to Looker, Tableau, and dbt.

An unofficial MCP server for generating infographics and visuals from text using the Napkin AI API, enabling AI assistants to create professional diagrams, mindmaps, and charts.

Turns a local CSV or XLSX table into a full analysis report — summary statistics, duplicate and missing-value diagnostics, top category frequencies, significant pairwise correlations, a Markdown insights writeup, and an Excel workbook with native interactive charts — entirely offline with no uploads, API keys, or pandas dependency. It runs over stdio or streamable-http behind a free anonymous tier that returns an in-band quota signal rather than silently billing.