"scikit-learn" matching MCP servers:

MCP server that lets AI assistants access University of Waterloo LEARN course data (announcements, content, grades, assignments, outlines) and search past assessments in Google Drive.

An MCP server that gives desktop AI apps access to your Waterloo LEARN courses, enabling listing courses, getting announcements, content, grades, and upcoming events through natural language.

MCP server that converts URLs into token-minimized clean text for LLMs, providing a receipt of token and cost savings.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.

An MCP server that makes your AI agent learn and evolve by capturing feedback as reusable, persistent skills that improve over time.

Enables AI assistants to search blog posts and pages from Ghost, and learn pages, case studies, and events from Contentful. Provides five search tools with contextual snippets via MCP stdio transport.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.

Distills Claude Code's 310K-line source into 32 queryable modules via MCP, enabling AI agents to learn and reuse Claude Code's architectural patterns through natural language.

MCP server for persistent, compounding memory that automatically captures corrections and insights across AI sessions, enabling agents to learn and improve over time.

Enables LLM agents to interact with the Lean theorem prover through the Language Server Protocol, providing tools for analyzing Lean projects, accessing diagnostics, goal states, documentation, and searching for theorems using both local and external search services.

A package manager for AI agents that connects LLMs to a global registry of capabilities, allowing them to autonomously discover, install, and learn new skills from a centralized repository.

Provides educational tools for developers to learn programming concepts, review code, get best practices, compare approaches, generate learning paths, debug, explain code, and quiz themselves.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Enables Claude to remember conversations and learn over time by storing and recalling messages, memory abstracts, and recent history using a local SQLite database.

REST API and MCP server for AI agents to extract structured LinkedIn profile data.

A Model Context Protocol server that gives AI coding agents 16 tools to secure what they build: install the one-line Nemesis Shield SDK, learn/approve/enforce app protection, put a domain behind a Cloudflare-like edge, guard LLMs (OWASP LLM Top 10), and create + score Omniguard business-logic fraud rules. Runs locally over stdio; the discovery tools work with no account.

An MCP server for agent-guided DSA practice that generates LeetCode-style problems and provides tutoring with escalating hints, concept explanations, and progress tracking.

Shared memory layer for AI coding agents to store and recall learned information across sessions and tools.

Enables AI agents to learn from their sessions by inspecting history, proposing rules or skills, and automatically persisting them to configuration files.

Enables low-cost agent models to control Windows applications through a compact, state-safe proxy over Open Computer Use, reducing model-visible context by up to 99.8% with support for record/replay and reusable UI component memory.