rohitg00/agentmemory

#1 Persistent memory for AI coding agents based on real-world benchmarks

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Summary Information

Updated 41 minutes ago
Added to GitGenius on May 16th, 2026
Created on February 25th, 2026
Open Issues & Pull Requests: 483 (+0)
Number of forks: 2,327
Total Stargazers: 27,233 (+0)
Total Subscribers: 77 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 16.7 hours
Mean response time: 6.4 days
90th percentile: 19.3 days
Tracked items: 356

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 95% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "security" is answered fastest, typically in about 2 hours, while "performance" waits about 2 weeks. 15% of tracked open issues have had no activity in three months. Only 13% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 262
New in 7 days: 20
Closed in 7 days: 1
Avg open age: 7 days
Stale 30+ days: 182
Stale 90+ days: 40

Recent activity

Opened in 7 days: 13
Closed in 7 days: 1
Comments in 7 days: 11
Events in 7 days: 16

Top labels

  • medium (29)
  • enhancement (27)
  • high (17)
  • security (12)
  • bug (11)
  • performance (11)
  • low (9)
  • good first issue (6)

Detailed Description

AgentMemory is a TypeScript-based persistent memory system designed specifically for AI coding agents, built on the iii engine and positioned as the top solution based on real-world benchmarks. The project provides memory persistence across multiple popular coding agents including Claude Code, GitHub Copilot CLI, Cursor, Gemini CLI, Codex CLI, Hermes, OpenClaw, and any MCP client, eliminating the need for users to repeatedly explain context to their agents.

The repository demonstrates substantial real-world adoption and engagement.

The system achieves measurable performance improvements in agent interactions. According to the README, AgentMemory delivers 95.2 percent retrieval accuracy at R@5, reduces token usage by 92 percent compared to baseline approaches, provides 53 MCP tools for integration, includes 12 automatic hooks for seamless agent integration, requires zero external databases for operation, and passes over 1,423 tests.

AgentMemory is distributed via npm as the @agentmemory/agentmemory package and supports installation through multiple pathways. The fastest installation method directs users to follow instructions at a dedicated INSTALL_FOR_AGENTS.md file that automates end-to-end setup and verification. Alternative installation options include npx execution without local installation, with version management handled through cache clearing if needed. The project maintains compatibility with existing iii engine installations by pinning to iii-engine v0.11.2 and refusing to attach to different versions due to protocol incompatibility.

The project's scope extends across multiple integration points. It functions as an MCP server, includes a real-time viewer for memory inspection, integrates with the iii Console for advanced management, and exposes both REST API and programmatic interfaces for agent integration. The system supports multiple languages in its documentation, with README translations available in Simplified Chinese, Traditional Chinese, Japanese, Korean, Spanish, Turkish, Russian, Hindi, Portuguese, French, and German, indicating international adoption and community contribution.

The repository maintains connections to related projects through shared contributors, linking to openclaw/openclaw, nousresearch/hermes-agent, and yeachan-heo/oh-my-claudecode, suggesting an ecosystem of complementary agent-focused tools and frameworks.