# AgentRecall-MCP

> Use this tool when you need to enhance your AI agent's session memory and improve its decision-making capabilities through think-execute-reflect quality loops. AgentRecall-MCP solves problems related to session persistence and knowledge retention, allowing agents to learn from past experiences and adapt to new situations. It integrates with git, accepting input from various data sources and outputting refined decision-making models.

Canonical page: https://skillsregistry.net/skills/goldentrii-agentrecall-mcp  
JSON: https://api.skillsregistry.net/v1/skills/goldentrii-agentrecall-mcp

## Description

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

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [GitHub](https://github.com/Goldentrii/AgentRecall-MCP)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "goldentrii-agentrecall-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/goldentrii-agentrecall-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/goldentrii-agentrecall-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt