"Performing Email-Related Operations in Python" matching MCP servers:

An MCP server that provides structured analytics for email data by extracting signals like topic, tone, and urgency using a local LLM. It allows users to query email distributions, sender patterns, and specific signals through a SQLite-backed interface.

Read-only MCP server for the July 2026 survey of AI in open-source design systems, enabling agents to query 19 systems' affordances, coercion techniques, and platform data via 9 tools, 2 resources, and 2 prompts.

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 to run structured QuReDec decision briefs from inside MCP-compatible clients, submitting questions and receiving evidence-backed recommendations with citations.

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

Real human judgment as agent tools -- an AI agent can ask a question and get back a structured, schema-validated JSON answer from a real quality-scored human. 16 response types (yes/no, ratings, rankings, A/B tests, sentiment, image/video/audio review, voice/video/photo capture). Fully programmatic signup with a $5 free trial credit, no card required.

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.

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.

Detects whether a company runs cold email outbound and identifies the email sending infrastructure, including sending domains, platforms, and authentication status.

Provides AI assistants with access to real-time space weather data and forecasts from NOAA's Space Weather Prediction Center, enabling queries and interpretations of geomagnetic storms, solar flares, and related indices.

MCP server for the Mamba Labs People Finder & Email Verifier actor on Apify. Give it a company domain, name or LinkedIn URL and it returns the people at that company who match your role, seniority and department filters, each as a structured contact record with an optional verified business email.

Enables querying Google Trends data directly from conversational MCP clients, including search interest over time, related queries and topics, regional breakdowns, and trending searches, for market research without leaving the chat.

Google Trends data: interest over time, by region, related queries, and trending now.

QuantContext turns plain-English strategy descriptions into executable quant research by screening stocks, backtesting, and performing factor analysis using real market data.

Enables searching and retrieving articles, citations, and structured content from Grokipedia for research and information retrieval. It provides specialized tools for section extraction, related page discovery, and filtered search results.

Enables querying Yandex Wordstat search statistics, including frequency, related queries, seasonality, and regional distribution, through natural language in AI clients.