"How to create pie and line charts with MCP" matching MCP servers:

An MCP server that enables AI agents to query RevenueCat's subscription analytics API using natural language, retrieving metrics like MRR, churn, and revenue.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

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.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Enables AI clients to search a local literature library via vector semantic retrieval, with automatic conversion of Zotero items and arbitrary files into Markdown (including OCR for scanned PDFs). It supports natural language queries and provides answers with page-level citations.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

Enables any agent to query the same interview corpus as the UI over stdio, exposing tools to list transcripts, search quoted lines, retrieve verified themes with citations and dropped reasons, and fetch source lines.

Query iOS App Store revenue and download estimates for any app directly from your agent. Two tools: estimate_app returns monthly revenue and downloads with a confidence label (verified / calibrated / modeled), and search_apps resolves an app name to its App Store id.

Custom MCP server for NotebookLM that adds audio source upload, YouTube source ingestion, source readiness polling, and transcript export, complementing standard Q&A and audio overview tools.

Enables coding agents to check what already exists, identify duplicate projects and missing features, and prepare merge plans or targeted outreach for overlapping work, with human approval before any message is sent.

Enables searching and discovering machine learning papers, state-of-the-art benchmarks, tasks, datasets, methods, and leaderboards from Papers with Code. Supports mapping papers to their benchmark results and browsing evaluation tables.

Give AI agents cited funding, money-market, FX and capital-market evidence through 16 public MCP tools. Keep source dates, freshness checks and coverage gaps attached; China macro coverage is metadata-only. No API key is required for the public surface. Research context only; no trade execution.

CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.

Classifies company sites as B2B or B2C and as SaaS, online store, agency, manufacturer, wholesaler, distributor, or marketplace, while matching your own buyer phrases and returning the quoted text and page as evidence. Runs deterministically on Apify, giving one row per domain with grace-free status rows for unreachable, blocked, or empty sites.

An MCP server providing progressive discovery tools for SDMX statistical data, enabling AI agents to explore and access SDMX-compliant repositories through interactive tools, resources, and prompts.

Deterministic US equity-compensation tax optimizer. Six tools cover ISO/AMT exercise scheduling, NSO sell-vs-hold, RSU vest-and-sell, single-stock concentration, protective put / zero-cost collar pricing, and Section 1202 QSBS qualification. Federal plus 50-state plus DC tax math.

One-call Australian health and welfare data plumbing via AIHW — cited responses for practical analysis, not a data broker.

Given a company domain or name, it checks ten app marketplaces — HubSpot, Salesforce AppExchange, Slack, Zapier, Shopify, Atlassian, Chrome Web Store, Microsoft, Google Workspace, and WordPress — to report where the company is listed, with each listing's URL, installs, rating, review count, and match confidence. Useful for competitive research and partner-ecosystem audits across many domains in a single run.

Enables users to pull portfolio company lists from Y Combinator, a16z, Sequoia, Accel, and other investors or any portfolio page URL, returning one row per company with name, domain, website, description, and stage or batch. Runs on Apify and produces Clay-ready output, with YC results filterable by batch, industry, region, status, and search terms.

Enables turning a research topic keyword or OpenAlex topic ID into ranked institutions and authors, including identifiers, citation metrics, h-index, and newest papers, with optional filters for year, country, and institution type. It runs the analysis on Apify and returns dataset rows to MCP clients.

An MCP-native pipeline for collecting structured intelligence on higher education institutions using the WHED schema, enabling scraping, extraction, validation, and saving of profiles.

Enables MCP clients like Claude to subscribe to RSS/Atom feeds, list feeds with unread counts, fetch and search new items, and mark items as read, all scoped to the authenticated user's account.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Enables AI agents to query free biomedical and pharmaceutical APIs for clinical trials, drug data, molecular structures, adverse events, and research literature.

Enables researchers to turn property-history questions into reviewable evidence dossiers by gathering sources, tracing people and places, linking conclusions to supporting or opposing passages, and exporting portable backups.

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

Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

Enables generation of various chart types (bar, line, pie, scatter, radar, heatmap, and more) using ECharts library, returning preview URLs to visualize data through natural language requests.

Transforms CSV data into beautiful visualizations including line charts, bar graphs, pie charts, and world maps. Returns base64-encoded PNG images optimized for AI chat interfaces and assistants.