"Using a search engine to find evidence to answer a question" matching MCP servers:

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

Enables AI assistants to create Evidence reports and dashboards by providing tools to query database schema, read documentation, edit pages, and debug code.

A graph database MCP server that lets AI assistants build, analyze, and visualize relationship graphs with algorithms like PageRank and cycle detection.

A local, fully vectorized computational engine for stock market analysis that enables AI to perform factor calculation, strategy backtesting, IC analysis, and GPU-based multi-dimensional visualization using local DuckDB data.

Enables local offline machine learning workflows, including CSV profiling and cleaning, classifier and neural network training, hyperparameter optimization, evaluation metrics, confusion matrix plots, Streamlit dashboards, and HTML reports through MCP tools.

Enables natural-language-driven analytics over CSV/Parquet or built-in data by decomposing questions into analytical tasks, running them via deterministic DuckDB and SciPy tools, and publishing only claims verified against the underlying rows.

A statistical analysis MCP server offering 30 tools for descriptive statistics, hypothesis tests, regression, and time series, all returning Markdown reports with automatic interpretations to enable AI agents to perform comprehensive data analysis.

Enables AI agents to perform deterministic search synthesis and compile Sparkpage layouts into comparison matrices and ready-to-render HTML interfaces through a zero-dependency Python MCP server. Plugs into Claude Desktop, Cursor, and other MCP clients for structured, low-latency output with execution telemetry.

Enables AI agents to perform dynamic search synthesis and compile Sparkpage layouts into comparison matrices and HTML interfaces, running deterministically with zero external dependencies over the Model Context Protocol.

Connects Google Search Console to AI assistants, enabling SEO data analysis through natural language conversations.

An HTTP MCP server for exploring CSV files that masks PII before any code execution, enabling safe data analysis with local or cloud LLMs.

Enables searching Google Scholar papers with year filtering, deduplication, and proxy support. Also provides paper detail retrieval, TF-IDF relevance analysis, and chart generation via MCP tools.

Enables AI assistants to read and modify Power BI Desktop files programmatically, including querying models, creating measures, and managing relationships through natural language.

Renders word-sized charts — sparklines, bars, bullets and 100+ more types — to self-contained SVG with generated alt text, small enough to sit inline in a model's reply or a table cell. Three tools: find the right chart for a question, get its wiring, and render it.

Integrates with Google Search Console to enable querying search analytics, comparing performance periods, generating visual reports, and identifying SEO optimization opportunities through natural language.

Enables conversational spatial SQL queries in plain English, turning natural language questions into validated PostGIS operations and rendering results as GeoJSON on an interactive map.

Enables read-only analysis of FST waveform files, including signal value queries, timing measurements, event search, latency analysis, and PNG plot generation using human-readable time addressing.

Enables rendering, validation, formatting, and inspection of D2 diagrams via the Model Context Protocol, using WASM for rendering without requiring the d2 binary.

Calculates Taiyi Shenshu (太乙神數) based on a given datetime and returns structured text and a board PNG image.