"Project dependency resolution and analysis" matching MCP servers:

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

Provides comprehensive statistical analysis tools for industrial data including time series analysis, correlation calculations, stationarity tests, outlier detection, causal analysis, and forecasting capabilities. Enables data quality assessment and statistical modeling through a FastAPI-based MCP architecture.

An MCP server for data analysis and visualization supporting CSV and Excel files. It enables users to generate statistical summaries and create multi-dimensional charts like heatmaps and bar plots through natural language.

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.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

A Python-based FastMCP server that provides financial tools for securities analysis, including market data, news, fundamental/technical analysis, and visualization capabilities that can be consumed by any MCP-aware client.

Enables comprehensive analysis of CSV files and SQLite databases through tools for statistics, correlations, anomaly detection, pivot tables, time series analysis, visualization, and automated insights discovery.

Enables LLMs to retrieve, analyze, and visualize stock prices and financial report data for quantitative trading research and investment analysis. Provides real-time and historical stock data, financial statement analysis, key metric calculations, and trading signal visualization.

Enables collecting data from configurable sources such as Jira, SonarQube, Uptime Robot, npm audit, and HTTP endpoints, then exporting it to an Excel file with one sheet per source.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Enables comprehensive stock market analysis with portfolio management, technical indicators, dividend tracking, sector analysis, risk metrics, and price alerts. Provides real-time stock data, trend analysis, and investment insights through natural language interactions.

An AI-driven tool for processing survey data that supports cross-tabulation, NPS and satisfaction scoring, and automated Excel report generation. It enables users to analyze datasets via natural language for tasks like merging response options and identifying demographic differences.

Enables real-time stock market analysis through AKShare API integration. Supports retrieving live stock prices, historical data, technical indicators (MA, MACD, RSI), market sentiment analysis, stock search, and financial news.

Enables users to convert a vendor partner directory (such as PartnerPage or the Shopify Partner Directory) or a trade body member list into one company row per listing, each carrying website, domain, tier, tags, and location for Clay-ready output. It runs the extraction on Apify, returning dataset rows for up to 20 directory URLs with optional deduping, detail enrichment, and a cost cap.

Enables an AI assistant to answer customer-success questions by synthesizing simulated billing, support ticket, and product usage data into composite churn-risk scores, bands, and plain-language explanations for fictional accounts. It exposes raw-data tools, a synthesis tool, and a methodology resource so users can list at-risk accounts or get a per-account health summary.

Enables querying and mutating data across multiple sources (CSV, Google Sheets, SQLite, PostgreSQL, MySQL, MongoDB, Oracle) through a dynamic GraphQL API, with flexible filtering, batching, persisted queries, and dynamic source switching.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

Provides real-time and historical cryptocurrency market data from multiple exchanges (Binance, Kraken, Coinbase Pro) with Redis caching and rate limiting support.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.