"Information about SQLite: a lightweight database engine" matching MCP servers:

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

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.

A secure multi-database MCP server supporting MySQL, PostgreSQL, and SQLite with read-only enforcement, SQL injection prevention, and tools for schema analysis, performance optimization, and visualization.

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.

A lightweight MCP server for tracking personal expenses, income, and budget summaries using SQLite.

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

Embeds live, interactive Tableau dashboards in ChatGPT, pushing mark selections to the model so questions about specific data points are answered with live queried numbers.

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.

Enables querying Tableau lineage through the Metadata API via MCP, supporting impact analysis, where-used lookups, and content search. Provides read-only tools for answering natural-language questions about workbooks, datasources, fields, and dependencies.

Enables querying SQLite databases in plain language through MCP, letting clients like Claude Code inspect schemas and run read-only SQL.

Geneva MCP brings production-grade forecasting directly into AI assistants and coding agents. Connect any MCP-compatible client to the Geneva Forecasting Engine and run rigorous time series forecasts through natural conversation.

Computes biorhythm values (physical, emotional, intellectual) and generates a PNG chart showing sine curves based on birth date and optional target date.

Visualizes conversations as structured hierarchical mind maps by injecting a prompt that instructs the LLM to generate a JSON mind map — no external APIs required.

A Model Context Protocol (MCP) server that exposes tools for exploring and querying SQLite and PostgreSQL databases. It allows Large Language Models (LLMs) to inspect table structures, perform statistical profiling, generate entity-relationship diagrams, and execute queries safely.