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.
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.
Enables time series analysis following Box-Jenkins-Treadway methodology, supporting guided or autonomous modes for model identification, estimation, and diagnosis via an LLM.
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.
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.
Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.
Converts Digital Object Identifiers (DOIs) to BibTeX format using the official DOI content negotiation API, enabling users to quickly generate bibliography entries for academic papers.
Enables searching and retrieving UK research grants, award values, institutions, and publications from the UKRI Gateway to Research API without authentication.
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.
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 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.
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.
Provides free Google Trends data (interest over time, term comparison, related queries, trending now, regional breakdown) to MCP-compatible AI clients without needing an API key.
An MCP server for the Open Food Facts API that allows users to search, read, and contribute to a global food database. It enables looking up nutrition data by barcode or name and managing product information through natural language.