"Learning or Writing Code in Python" matching MCP servers:

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

Provides access to the Korean elementary 2022 revised curriculum learning graph, enabling users to search and retrieve curriculum standards, learning topics, prerequisites, and roadmaps from a fully local database.

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.

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.

Enables LLMs to generate visual summary reports from CSV datasets using MCP Resources, Tools, and Prompts, without exposing raw data to the model.

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

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 operate DSpace repositories through a typed interface, including SAF package building, metadata editing, scientometric harvesting, open-access PDF downloads, and repository administration.

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.

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.

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 tools to search and execute Code Ocean capsules and pipelines while managing platform data assets. It enables users to interact with Code Ocean's computational resources and scientific workflows directly through natural language interfaces.

Enables MCP clients to fetch live football odds and team form, and flag matches where the market price diverges from a simple form-based estimate.

Enables AI clients to query ContentRadar data and write low-risk content using natural language, with 15 tools for monitoring, analysis, and content management.

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.

An MCP-native research assistant — search backend, intent-routing, and writing pipeline that carries a question through search, verification, and writing, delivering whatever research you need: quick answers, verified sources, or a finished document.

MCP server that analyzes your writing style to generate personal voice rules, scores drafts for AI slop, and verifies authorship, enabling LLMs to write in your specific voice.

MCP server pulling academic publications (arXiv, PubMed, HF Daily Papers), trending code (GitHub, HF Hub), and medical-device regulatory data (FDA 510(k), recalls) into newspaper-style briefings. Per-category round-robin, weighted configuration, sandbox-safe Python launcher.