"Video content analysis and understanding for large language models" matching MCP servers:

A production-grade MCP server that provides tools to fetch historical stock data, company information, and technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) via yfinance, and includes a Flask web dashboard for visual analysis.

Read-only MCP server that lets analysts pull Yahoo Finance data and compute risk metrics, technical indicators, fundamental and peer ratios, ETF tracking statistics, plus user-defined parametric indicators, conditions and saved hooks with chart output. Every result carries its unit, formula source, data window and warnings, so the agent can explain each number.

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

An MCP server that answers natural-language questions over CSV, Excel, and SQL data by providing deterministic tools for loading, profiling, querying, cleaning, statistical analysis, visualization, and reporting. It enables LLMs to plan and interpret while all computation is done exactly through MCP tools.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Provides aerodynamic analysis tools through MCP, enabling geometry generation, meshing, CFD solving, and visualization for 2D airfoils.

Enables Claude to retrieve real-time financial data, extract ESG risk metrics for S&P 500 companies, and generate automated analytical visualizations through three integrated MCP tools.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Enables end-to-end analysis of Reddit discussions: fetches posts, performs sentiment and toxicity detection, generates visualizations and word clouds, and optionally builds Neo4j knowledge graphs, all through natural language orchestration.

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.

Provides a local stdio MCP interface for Apache ECharts infrastructure, enabling language models and agents to access chart-related tools and resources.

Enables your own ChatGPT to build and manage a collaborative work board—dashboards, categories, datasets, monitors, and policies—through typed WebMCP tools, with human approval, audit trails, and guardrails enforced on every action.

Exposes semiconductor wafer analysis tools including wafer maps, P-charts, and statistical plots, enabling AI assistants to visualize and analyze wafer test data.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.

Enables Claude to read a project's FastStats metrics and then design, validate against real data, and publish charts, dashboards, event markers, and custom data sources. Every write is previewed and dry-run first, with read-only mode and confirmation guards for destructive actions.

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.

MCP server for Microsoft Power BI and Fabric, enabling Claude to discover workspaces, semantic models, generate and execute DAX queries, and retrieve report metadata via device-code authentication.

Google Search Console for Claude and other MCP clients. Sign in with Google in one click, then ask about clicks, queries, rankings and indexing, export every GSC report as CSV (beyond the 1,000-row UI limit), inspect URLs, submit sitemaps and verify sites. Includes a local SEO dashboard. Free, open source, runs on your computer.

Enables AI agents to query Google Trends for search-interest signals, returning stable JSON envelopes with calibrated searches/day estimates, relative comparisons across keywords, related and rising queries, regional interest, and country-level Trending Now data. It also surfaces explicit status and error codes so agents can distinguish partial or failed results from real numbers.

Enables AI assistants to drive a live TradingView chart in Chrome, turning natural-language trading ideas into compiled Pine Script indicators, adding them to charts, and reading back results. It also supports chart navigation, indicator management, screenshots, and strategy tester backtest results.

MCP server providing data analytics tools for AI agents to load, clean, analyze data, generate charts and dashboards.

Enables AI assistants to control a logged-in TradingView chart in Chrome, including writing and compiling Pine Script indicators, adding them to charts, changing symbols and timeframes, capturing screenshots, and retrieving strategy tester results.

Options analytics an agent can drive: import a permitted chain, solve implied volatility, build a sixteen-Greek ladder, map dealer gamma walls, rank twenty-three structures, run a GARCH-t simulation with a convergence gate, and backtest with modelled premiums. Twelve stdio tools; every output is a schema-validated JSON file with source, assumptions and a degraded flag. Research only, no orders.

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 LLMs to discover, understand, and generate Teal R Shiny applications for clinical trial data analysis.

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 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.

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.

Renders OHLCV data as candlestick chart PNGs and returns inline images. It is a pure renderer with no network access, allowing models to view charts generated from provided data.

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