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Agent Memory

ChatGPT plugin

Memory across coding sessions

View in ChatGPT directory

Recall past decisions, resume work, save useful context, and learn from corrections across your coding sessions using one local Agent Memory daemon. Includes search, session history, lessons, graph queries, memory maintenance, export, and deletion workflows. Requires Node.js 20+ and a running Agent Memory daemon. Basic keyword recall needs no model key. Embeddings and model-based features require configuration; external providers may receive selected data when enabled. This package contains the skills only. Install the Agent Memory daemon and wire its MCP server with `agentmemory connect codex` so the skills can call the memory tools. Designed for local Codex sessions.

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#10649of 10,70456places down24h—7d
#10,004#10,181#10,358#10,535Oct 4Oct 10Oct 16Oct 22Oct 28Nov 2

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#848of 8667places down24h—7d
#804#816#828#840#852Oct 4Oct 10Oct 16Oct 22Oct 28Nov 2

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Developer tools848th of 866 by placement
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846Mobile Dev#106461,922places down
847Cross-LLM Delivery#10647—
848Agent MemoryThis page#10649—
849Kangaroo Rewards API#106531,923places down
850PIO Agent#106631,898places down

All 866 Developer tools plugins

Example prompts

  • “Check my local Agent Memory connection and explain which features are enabled.”
  • “Recall decisions relevant to this repository, with the evidence for each.”
  • “Resume the latest session for this repository and show the recorded next step.”

Skills

  • agentmemory-agents

    How agentmemory wires into host coding agents via the connect command. Use when installing agentmemory into a specific agent, when asked which agents are supported, or when a connect adapter writes the wrong config path.

  • agentmemory-architecture

    How agentmemory is built, the iii engine primitives it runs on, its storage model, ports, and the viewer. Use when reasoning about how memory is stored or retrieved end to end, when extending the system, or when answering how agentmemory works under the hood.

  • agentmemory-config

    Set up and diagnose local agentmemory, including MCP, environment variables, ports, and feature flags. Use when getting started, checking a connection, enabling a feature, configuring auth, or explaining why a feature is off by default.

  • agentmemory-hooks

    The agentmemory plugin hooks that capture observations automatically across the agent session lifecycle. Use when explaining how memory gets captured without manual saves, when debugging missing observations, or when tuning what gets recorded.

  • agentmemory-mcp-tools

    Map of every agentmemory MCP tool, what each does, and its parameters. Use when choosing which memory tool to call, when a tool name or argument is unclear, or when answering what agentmemory can do via MCP.

  • agentmemory-rest-api

    The agentmemory HTTP REST API surface, the primary protocol for talking to the memory server. Use when calling agentmemory over HTTP, when MCP is unavailable and you need a fallback, or when integrating a host that does not speak MCP.

  • commit-context

    Trace a file, function, or line back to the agent session that produced its current commit. Use when the user asks "why is this code here", "what was the agent doing when this changed", "who wrote this", or wants context on a specific location in the codebase.

  • commit-history

    List recent git commits linked to agent sessions, optionally filtered by branch or repo. Use when the user asks "show agent commits", "what has the agent shipped", "list linked commits", or wants commits with their session context.

  • forget

    Delete specific observations from agentmemory after showing them and getting explicit confirmation. Use when the user says "forget this", "delete memory", "remove that note", or wants to scrub specific data for privacy.

  • handoff

    Resume the most recent agent session for the current working directory, leading with any unanswered question. Use when the user says "where were we", "resume", "handoff", "pick up where I left off", or starts a session with no fresh context.

  • lesson

    Save a correction or hard-won rule as a confidence-weighted lesson that resurfaces before similar work. Use when the user corrects your approach, says "learn this", "always" or "never do X", or you notice yourself repeating a past mistake.

  • memory-discipline

    The session loop that makes agentmemory pay off, recall before starting work, save at decision points, learn from corrections. Use when starting a nontrivial task, after settling a decision or debugging a gotcha, or whenever deciding if something belongs in memory.

Show all 17
  • recall

    Search agentmemory for past observations, sessions, and learnings about a topic using hybrid BM25 plus vector plus graph search. Use when the user says "recall", "what did we do about", "did we ever", "have we seen", or needs context from past sessions.

  • recap

    Summarize the last N agent sessions for the current project, grouped by date, with highlight observations per session. Use when the user asks "recap", "what have we been doing", "today", "this week", or wants a rollup of recent work.

  • remember

    Save an insight, decision, or learning to agentmemory's long-term storage with searchable concept tags. Use when the user says "remember this", "save this", "note that", "don't forget", or wants to preserve knowledge for future sessions.

  • session-history

    Show what happened in recent past sessions on this project as a clean timeline. Use when the user asks "what did we do last time", "session history", "past sessions", or wants an overview of previous work.

  • write-agentmemory-skill

    The house format and rules for writing or updating an agentmemory skill. Use when adding a new skill, restructuring an existing one, or reviewing a skill contribution for consistency.

Categories
Made by
Rohit Ghumare · Website
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On Install
Capabilities
Local persistent memory, Session handoff, Lessons and recall, Memory management
Availability
Available
Version
0.9.30
Created
October 6, 2026
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