Local-first personal AI identity and memory for MCP-compatible coding tools — lessons, decisions, playbooks, and project context you can see, edit, and override.

Never lose context again - persistent memory management system for AI-powered workflows across multiple tools

Long-running fleet orchestration and memory infrastructure for AI agents. Enables persistent context, shared memory, task execution, and governed coordination across multi-agent systems.

Multi-agent memory governance demo using MemClaw + OpenClaw. Three agents (Sales, Legal, Admin) share one memory backend with hard fleet boundaries enforced at the query layer. Shows scoped writes, blocked recall, cross-fleet synthesis, and conflict detection.

Privacy-safe context receipts for AI coding agents: prove what context, memory, tools, skills, compactions, and security findings crossed the boundary without logging raw content.

Share your context sessions across Claude Code, Codex, and OpenCode. With zero token cost.

Lightweight MCP server for sharing project context between AI agents across machines

One memory. Every AI tool. Yours to keep. Local-first, MCP-compatible, Apache 2.0.

One memory. Every AI tool. Yours to keep. Local-first, MCP-compatible, Apache 2.0.

One memory. Every AI tool. Yours to keep. Local-first, MCP-compatible, AGPL-3.0.

An MCP server for orchestrating multi-agent workflows inside herdr, enabling real-time communication, pane management, and contextual handoffs.

One memory. Every AI tool. Yours to keep. Local-first, MCP-compatible, Apache 2.0.

Export and share development state for seamless handoffs between humans and AI

One memory. Every AI tool. Yours to keep. Local-first, MCP-compatible, AGPL-3.0.

One memory. Every AI tool. Yours to keep. Local-first, MCP-compatible, Apache 2.0.

Shared-context MCP bridge for cross-IDE AI workflows in VS Code, IntelliJ, Visual Studio, and more.

Our planner has context sharing,in process MCP tool integration,structured output using pydantic(md,json), Task monitoring & Logging using callback functions, A2A protocol and used interoperability - e.g. one agent defined using ADK another using CrewAI.