episode-complete

A self-learning episodic memory system built in Rust that provides persistent memory across agent interactions through an MCP server, with semantic pattern search, embeddings, and optional sandboxed WASM code execution.

A skill from the Rust Self-Learning Memory System, which provides persistent episodic memory across agent interactions through an MCP server with semantic pattern search, embeddings, and optional sandboxed code execution.

Part of the Rust Self-Learning Memory System, which provides persistent episodic memory across agent interactions with semantic pattern search, embeddings, and an MCP server. Includes strict code quality gates with zero clippy warnings, formatting checks, security audits, and semver verification.

A context retrieval skill from the Rust Self-Learning Memory System, providing persistent episodic memory with semantic pattern search, embeddings, and an MCP server for AI agent interactions.

Part of Rust Self-Learning Memory System, an MCP server providing persistent episodic memory across agent interactions with semantic pattern search, embeddings, and optional sandboxed WASM code execution. This skill leverages Perplexity's reasoning capabilities for deep research tasks within the memory system's learning and retrieval workflow.

A production-ready Rust-based self-learning episodic memory system for AI agents, featuring an MCP server with semantic pattern search, multi-provider embeddings, and a secure code execution sandbox.

A skill from the Rust Self-Learning Memory System, an MCP server providing persistent episodic memory with semantic pattern search, embeddings, and optional sandboxed WASM code execution for AI agents.

Part of the Rust Self-Learning Memory System, which provides persistent episodic memory across agent interactions via an MCP server. Features pattern recognition with semantic search, episode lifecycle management, multiple storage backends (Turso/libSQL, redb, SQLite), and WASM-sandboxed code execution.

A Rust-based self-learning episodic memory system for AI agents that captures, stores, and learns from experiences through semantic pattern search, embeddings, an MCP server, and optional sandboxed code execution.

A Rust-based self-learning episodic memory system that provides persistent memory across agent interactions via an MCP server. It captures and learns from experiences using semantic pattern search, embeddings, and optional sandboxed WASM code execution.