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AgentRecall-MCP
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AgentRecall-MCP

Active·★ 258·MIT·Updated 2026-05-26
★ Trending★ Memory & Context★ Dev Tooling

Persistent, correction-driven memory for AI agents. Cross-session, cross-platform (Claude Code, Codex, Gemini — any MCP client). Learns from mistakes, compresses context to save tokens, consolidates knowledge overnight. npm: agent-recall-mcp

AgentRecall is a learning loop for AI agents that provides persistent, compounding memory. It captures corrections automatically, surfaces past insights across projects, and uses a five-layer memory pyramid with Ebbinghaus decay and Bayesian feedback. Zero cloud, all local markdown files.

#agent-memory#ai-agents#claude-code#intelligent-distance#mcp#mcp-server#mcp-servers#quality-loop
$ Install
$ claude mcp add --scope user agent-recall -- npx -y agent-recall-mcp
↗ Visit site★ GitHub
01

Features

01Persistent, compounding memory with 200-line awareness cap
02Automatic correction capture and alignment checking
03Cross-project insight recall via keyword and semantic (pgvector) search
04Zero cloud, all local markdown files, Obsidian-compatible
0510 MCP tools for agents, plus SDK and CLI
02

Compatibility

Claude Code
Claude Code
Verified via docs
Cursor
Cursor
Verified via docs
VS Code (Copilot)
VS Code
Verified via docs
Windsurf
Windsurf
Verified via docs
OpenAI Codex
Codex
Verified via docs
Claude Desktop
Claude Desktop
Verified via docs
03

Quick start

1
$ claude mcp add --scope user agent-recall -- npx -y agent-recall-mcp
04

Use cases

↳Maintain context across AI agent sessions (Claude Code, Cursor, etc.)
↳Capture and learn from user corrections in software development
↳Coordinate memory across multiple parallel agents
05

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Related searches

AgentRecall-MCP AlternativesBest Memory & Context Tools 2026Open Source Memory & ContextAgentRecall-MCP TutorialAgentRecall-MCP Vs Competitorsagent-memoryai-agentsclaude-code

Comments

Log in to leave a comment
  • H
    Harley HarrisMay 3, 2026

    Memory corrections propagate properly — the agent doesn't repeat corrected errors.

  • S
    Sage DavisApr 28, 2026

    Good for long-running agent deployments where accumulated knowledge matters.

  • O
    Oakley LewisApr 14, 2026

    Correction-driven memory means the agent gets smarter when you point out mistakes.

  • H
    Hayden ClarkMar 8, 2026

    Cross-session and cross-platform persistence is rare and valuable.

On this page
01Features02Compatibility03Quick start04Use cases05Alternatives
Stats
GitHub Stars★ 258
Last commit4d ago
StatusActive
LicenseMIT
CategoryMemory & Context
Trend (30d)
+10.3↑ 0.9%
Links
Documentation↗Discussion↗Issues↗Releases↗

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