AgentHelm
Shared memory & coordination layer for AI agent teams
AgentHelm launched on July 20, 2026 with 6 votes, #3,356 of 24,623 launches that month and more than 75% of that year's launches.
What it does
AgentHelm gives every AI coding agent a shared Project Brain — so Claude Code, Cursor, and custom agents all remember the same architecture, APIs, and decisions instead of starting from scratch each session. Unlike per-agent memory tools, it's one shared brain across unlimited agents. Built on open protocols (MCP, A2A), not a proprietary lock-in format. One Project. One Brain. Unlimited AI Agents
AgentHelm keeps autonomous AI agents safe in production: human-in-the-loop approvals, audit trails, budget guardrails, and a shared Project Brain — wrapped around any agent framework. India-first, powered by Sarvam AI.
AgentHelm wraps any agent framework with human-in-the-loop approvals, audit trails, budget guardrails, and a shared Project Brain — so autonomous agents stay accountable, on-budget, and recoverable. Every time your agent starts a new session, it begins with a blank slate. No memory of past decisions, configuration patterns, or API specifications. Agents don't remember project architecture, API choices, or database migrations. Every run starts from scratch. Engineering context is locked in single agent sessions. What one agent learns is lost to all others on the codebase. Without shared project standards, agents write code using deprecated functions or insecure library wrappers. AgentHelm…from agenthelm.online
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AgentmemoryMay 2026 · agent-memory.dev · ▲310Persistent memory for Claude Code, Codex & coding agents
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20+ Claude Code agents coordinating on real work (open source)Feb 2026 · github.com · ▲53Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…

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