"Tools for Converting LaTeX Mathematics to Lean Formalizations" matching MCP servers:

Enables verification of Lean 4 mathematical proofs via MCP tools, allowing AI clients to compile and check theorems with Mathlib.

An MCP server that renders LaTeX math expressions and step-by-step solutions into high-quality PNG images and hosted URLs. It enables AI assistants to provide visual mathematical solutions formatted for messaging platforms like iMessage.

An MCP server that enables MCP clients to directly access and process arXiv papers by fetching the LaTeX source, improving mathematical content understanding.

Enables MCP clients to fetch and process arXiv papers' LaTeX sources, providing full papers, abstracts, section lists, and specific sections for accurate interpretation of mathematical expressions.

Enables MCP clients such as Claude Desktop, Claude Code, and Cursor to fetch and process arXiv papers' LaTeX sources, allowing accurate interpretation of equations and mathematical expressions. Provides tools to retrieve full flattened LaTeX, abstracts, section lists, and specific sections by path.

Enables MCP clients such as Claude Desktop, Claude Code, and Cursor to fetch and process arXiv papers' original LaTeX sources, so equations and mathematical notation are interpreted accurately rather than garbled from PDFs. It exposes tools to retrieve a paper's full flattened LaTeX, its abstract, its section headings, or a single section by path.

Enables AI agents to subscribe to a deterministic daily ethics feed drawn from a four-module curriculum and retrieve read-only tools, resources, and reflection prompts covering principles, case studies, and codes of conduct.

An AI-powered study assistant that generates quizzes, flashcards, summaries, and concept explanations from study materials using the Model Context Protocol.

Evidence-first YouTube research server enabling search, transcript citation, video analysis, flashcards, and collateral generation for MCP hosts and VS Code.

An MCP server that wraps Aristotle's automated theorem prover for Lean 4, allowing AI assistants to fill in proofs, verify lemmas, and formalize natural language into Lean code.

Provides Latin NLP tools for tokenization, lemmatization, POS tagging, reported speech detection, and LiLa Knowledge Base querying via MCP.

Enables searching for upcoming academic conferences and events from WikiCFP by keywords, returning detailed information including dates, locations, submission deadlines, and related resources.

A local MCP study assistant that explains topics, creates study plans, and generates revision checklists through the Model Context Protocol.

Enables a study assistant to explain topics, build study plans, and generate revision checklists, with read-only access to course outline and status resources.

Enables Claude Desktop users at the University of Ghana to read their own Sakai courses through safe, read-only tools — checking deadlines, announcements, calendars, assignments, feedback and grades, and extracting text and page images from lecture slides for study, planning and revision.

Enables AI apps to read a student's Moodle courses, upcoming and overdue due dates, assignment submission statuses, course grades, gradebook items and announcements. It is strictly read only, so it can never submit, edit or delete anything.

Enables AI apps to read a student's courses, due dates, grades, missing work, announcements, modules, discussions, syllabus, and calendar events in a read-only way. It cannot submit, edit, or delete anything, and credentials go only to the user's own school.

Provides structured MCP tools for querying college database records, including student profiles, course details, enrollments, faculty teaching assignments, and academic statistics.

Enables querying of a locally pinned snapshot of the Education-to-Workforce Indicator Framework — 99 indicators and 11.8M observations — to browse questions, describe metrics, resolve places, and fetch or rank data across national, state, county, and district levels.

Enables AI agents to browse and teach the Deep Learning DIY course, providing access to modules, notebooks, transcripts, quizzes, slides, and homework via MCP tools.