"Using MySQL's MySQL Connector/Python (mcp) with Cursor" matching MCP servers:

Cursor plugin: Arch theological review API (POST /v1/review)

Enables AI agents to invoke the real browser Zotero Connector to connect to the current article page, trigger saves, and verify that PDF attachments actually landed, with status, download, and local-write authorization tools.

Enables AI agents to act as an individual user, within that user's live roles and firm policy, across LitKit document review, LitLex case-law research, and LitSpace matter files. Supports read operations such as searching and reading documents, opinions, citations, statutes, and files, plus immediate write actions like tagging documents, saving notes, posting to threads, and uploading files.

Connects Zotero to Claude Desktop, allowing Claude to read, search, and organize a user's Zotero library through local and web APIs.

MCP server that turns operator-authorized local or synthetic source records into auditable research briefs, with every finding linked to exact excerpts and hashes. Exposes a single build_research_brief tool over deterministic, no-network stdio.

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.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Enables users to search and fetch PubMed biomedical literature articles through natural language queries in Microsoft 365 Copilot.

Fetches, parses, and summarizes ETSI telecommunications and media standards documents, enabling Claude to autonomously look up and ingest standards mid-conversation for answering questions, generating conformant code, or writing XML.

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.

Integrates local Zotero libraries with Claude's Desktop interface, allowing users to access and manage their library collections via a local API.

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.

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.

A Python implementation of the Model Context Protocol (MCP) server that enables searching and extracting information from arXiv papers, designed to be extensible with additional MCP tools.

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.

Enables secure execution of statistical Python code in isolated micro-VM sandboxes, generating charts and analytical summaries.

Enables AI agents to hire verified human operators for tasks requiring physical presence, human perception, or judgment, such as real-world verification, product testing, and data collection.

Search and load AI fine-tuning and evaluation datasets, prompts and few-shot contexts from the ContexteTech catalogue, grounded in official European sources, in 9 languages. Dataset download links (JSONL, ShareGPT, Alpaca, CSV) and cost estimates per model.

Provides AI agents with real-time access to corporate credit data, including debt structures, bond pricing, and guarantor chains extracted from SEC filings. It enables complex financial analysis such as screening companies by leverage, tracing corporate hierarchies, and searching covenant language.

Enables time series analysis following Box-Jenkins-Treadway methodology, supporting guided or autonomous modes for model identification, estimation, and diagnosis via an LLM.

Enables AI assistants to load CSV datasets, compute summary statistics, filter rows, rank columns, and compute correlations through the Model Context Protocol.

Enables analysts to build and evaluate simultaneous VARMA models for systems of time series via exact maximum likelihood on the ATSW ladder, using univariate models as the yardstick. It guides users through loading univariate fits, identifying residual cross-correlations, estimating joint models, forecasting, impulse responses, variance decomposition, and recording decisions.

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

Enables patent management workflows inside AI tools, allowing users to capture and refine inventions, collaborate with attorneys, and access portfolio context through natural language.

Aggregates AI/ML/data-engineering developments from free public sources into a ranked, deduplicated, categorized feed for Claude.

Enables Cursor's AI to query live advertising data over a remote MCP endpoint — ads, advertisers, taxonomy, creative text, and spend/traffic/sales grades — after OAuth sign-in. Provides competitive intelligence as structured, reasoning-ready context rather than a raw data dump.

Provides tools to interact with the OpenCTI platform, including checking if a campaign exists.

Query 474 validated startup gaps from Claude Desktop, Cursor, and Windsurf.

Enables chatting with your site's SEO using real data, including crawling, on-page auditing, Google Search Console performance, Core Web Vitals, and competitor comparison from MCP clients like Claude or Cursor.

A safety-bounded MCP server for discovering data-acquisition devices and performing finite analog-voltage and digital-input reads through NI's nidaqmx Python package.