"Information about Python programming or Python-related topics" matching MCP servers:

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

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.

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

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

Provides access to Canadian federal parliamentary data (debates, bills, MPs, votes, Hansard transcripts) and legal information (case law and legislation through CanLII) for research and analysis.

Self-hosted MCP toolkit providing web search, Wikipedia, and arXiv access without mandatory API keys, delivered as a Docker Compose bundle.

A read-only reference server for 303 curated generative art algorithms implemented in Python (py5), spanning physics, fractals, cellular automata, shaders, and more. Agents can search by keyword, visual mood (ethereal, chaotic, crystalline…), or multi-layer artistic intent to discover algorithms, read structured summaries, and fetch bounded source snippets.

Calculates Vietnamese Tử Vi horoscope charts, generating structured JSON with Thiên Bàn and Địa Bàn, transit analysis, and local persistence via SQLite.

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.

An MCP server that guides Copilot to version-correct documentation and source code for Industrial Ecology Python packages, enabling reliable, environment-aware coding assistance for LCA workflows.

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

Seed oil (PUFA) data for 500+ US restaurant chains: letter grades, the oil each chain fries in, cleanest menu items, and rankings. Zero-dependency Python stdio server backed by the free hosted Seed Oil Tracker endpoint, no key or account needed.

A bridge connecting AI agents to NCBI's PubMed database through the Model Context Protocol, enabling seamless searching, retrieval, and analysis of biomedical literature and data.

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.

Enables MCP clients to search for published academic articles and retrieve detailed metadata, abstracts, citation counts, and related information from the Elsevier Scopus API. Supports citation verification and writing-style analysis grounded in peer-reviewed sources.

Enables MCP clients to fetch Google Trends data for any term, including interest over time, interest by region, and related queries and topics, all as structured JSON.

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.

Lets agents and chat clients load battery cells, collect them into frames, render figures, export data, look up cellpy API calls, and set up batch projects without writing Python.