"scikit-learn" matching MCP servers:

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

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 AI coding agents to evaluate code snippets and learn from execution outcomes through local bio-inspired associative memory, delivering instant zero-token bug and antipattern reflexes without LLM inference.

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

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

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

Failure Memory provides AI coding agents with a shared local memory of failures, enabling them to record, recall, and learn from mistakes across sessions.

Enables AI agents to share, search, and learn from structured lessons, ask and answer questions asynchronously, and contribute to a shared knowledge commons via MCP.

Enables persistent project memory for Hermes Agent by storing and retrieving wiki, code, and learning layers locally, with tools to recall, learn, retire, and ingest information beyond the context window.

An agent-native teaching OS that gives AI assistants a persistent classroom with courses, lessons, flashcards, and graded exercises via MCP tools.

Provides access to a community knowledge base of 16k+ debugging solutions and 223+ reusable skills, plus auto-scanned project-specific knowledge bases that learn and store solutions as you work.

An MCP server implementation that helps Claude remember and learn from programming errors by storing, retrieving, and finding similar errors with full context.

A productivity coaching assistant designed for ADHD support that provides intelligent task management, goal tracking, and personalized recommendations. It utilizes a persistent memory system to learn user patterns and preferences, helping to reduce decision paralysis through actionable suggestions.

Persistence memory MCP server that enables AI coding agents to recall and learn from past sessions, storing scars, wins, patterns, and decisions for continuous improvement.

Local workspace memory for Claude Desktop. Indexes documents into a vector store with hybrid search, cross-session memory, auto-learn, and knowledge graph.

Enables AI assistants to learn file organization rules, propose destinations for content, and manage those rules through MCP stdio tools, without writing files itself.

MCP server that lets you search your Claude Code conversation history to find past solutions, track file changes, and learn from previous work.

Enables file-based knowledge management with ranked keyword and semantic hybrid search, allowing AI agents to learn from documents and recall relevant knowledge as a persistent memory tool.

An MCP server that enables Claude to learn from user corrections by recording them as persistent rules in CLAUDE.md files. It manages project-specific or global guidelines to ensure the assistant avoids repeating the same mistakes in future sessions.

Intercepts Claude conversations via MITM proxy and stores them in Mem0, enabling Claude to search and recall past conversations, learn user preferences, and maintain context across sessions.