Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
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Solution for long term memory for agent coding CLIs and to facilitate handoff between different agent vendors
One shared memory for every coding agent on your team. Claude Code, Cursor and Codex get a map of your code and your team's past decisions, so they pick up where you left off.
- ai-agents
- claude-code
- code-graph
- context-engineering
Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows.
- agents
- claude-code
- claude-code-cli
- claude-code-hooks
Official Code of Memento: Fine-tuning LLM Agents without Fine-tuning LLMs
Agent memory: long-term memory & agent memory handoff. Claude Code & Codex.
- agent-memory
- claude-code
- codex
- self-evolving
Shared local memory, session history search, cross-agent handoff, and uncommitted code recovery across 43 coding agents — Claude Code, Codex, Cursor, OpenCode, Gemini CLI, OpenClaw & more (CLI & MCP). One Go binary, zero LLM calls.
- claude-code
- codex
- mcp-server
- cursor
Official repository for MemT-1.0
Official code for "Zero-Mem: Zero-Token Memory Operations for LLM Agents".
Agentic memory for CTI in Python — STIX knowledge graphs, threat-actor alias resolution, offline-first RAG, MCP server for Claude Code and LangChain agents
- claude-code
- cti
- llm
- rag