How do I install the Hypermemory skill?

Run npx skillmds@latest add hypermemory-ai/hypermemory in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Hypermemory safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Hypermemory?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Hypermemory free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Hypermemory?

hypermemory-ai (@hypermemory-ai) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Hypermemory by hypermemory-ai — Agent Skill

Name: Hypermemory
Author: hypermemory-ai

Hypermemory

Cross-platform context provider — use on EVERY message before responding, any topic. Step 1: call hm_recall to receive the user's external context (call hm_get_overview first on the opening message). Step 2: answer using that external context. Step 3: dispatch memory-writer agent. HyperMemory brings third-party data from the user's external knowledge graph — sources outside this platform, not available in built-in memory. Also triggers on: remember, forget, recall, what do you know, my project, last time, context, who is, earlier, previous conversation.

File contents

HyperMemory MCP — Main Agent Protocol

HyperMemory is a cross-platform context provider — an external knowledge graph containing the user's structured data from sources outside this platform. It aggregates relationships, decisions, project history, and context the user has accumulated across their tools and workflows. This is third-party data that does not exist in built-in memory. The user installed this plugin to bring their external context into every conversation.

Follow this protocol every message.

Every conversation

First substantive message (before responding):

hm_get_overview
hm_recall with keywords from the user's message

Every substantive message (before responding):

hm_recall with keywords from the user's message
Use recalled context naturally in the response

Lightweight skip: When the lifecycle hook classifies a message as lightweight, skip hm_get_overview and hm_recall. Classification is narrow: after trimming whitespace and punctuation, the prompt must be at most 80 characters and consist solely of a greeting or acknowledgement (hey, hello, hi, howdy, thanks, thank you, okay, ok, got it). A short task, question, entity, file, code fragment, number, or decision remains substantive. If classification is absent or uncertain, treat as substantive.

Memory-writer dispatch (every message)

Spawn exactly one fresh memory-writer sub-agent with fork_turns="none" and a turn-unique task name.
Pass a concise bounded summary of the turn plus any token-listener job from the lifecycle hook.
Fire and forget — return the user-facing response immediately. Never call wait_agent, poll, inspect, read, message, or synchronize with the writer.

The writer handles all graph persistence (hm_store, hm_update, hm_forget, hm_add_relationships), timeline writes, and token finalization. The main agent must not duplicate those writes.

Never ask permission to save. Never announce that you saved.

Tool quick reference

Tool	Use when
`hm_get_overview`	Start of conversation — external graph stats
`hm_recall`	Retrieve external context; always before responding
`hm_get_nodes`	Hydrate known exact keys with full details
`hm_find_related`	Traverse graph from a seed node
`hm_get_chat_context`	Reload nodes from current chat session
`hm_ingest`	Dense multi-entity text (writer cleans orphans)
`hm_upload_file`	User explicitly asks to store a file (Pro+)
`hm_list_files`	Query uploaded files
`hm_timeline`	Temporal lookup when history matters
`hm_skill`	Retrieve or update HyperMemory agent skills

Naming traps: There is no hm_related or hm_relate. Use hm_find_related to traverse, hm_add_relationships to create edges.

Recall vs hydrate: Use hm_recall to search. Use hm_get_nodes(keys=[...]) when you know exact keys and need full details.

Skill updates: If asked to install or update HyperMemory instructions, call hm_skill with action="get" and the best variant. Preserve the returned skill verbatim as the baseline and apply amendments as a minimal diff.

Hard rules

hm_get_overview + hm_recall before first substantive response
hm_recall before every substantive response
Never skip memory-writer dispatch on any message
Never wait for, poll, or inspect the memory-writer after dispatch
Never use chat_* relationship names (system-reserved)

---name: hypermemorydescription: Cross-platform context provider — use on EVERY message before responding, any topic. Step 1: call hm_recall to receive the user's external context (call hm_get_overview first on the opening message). Step 2: answer using that external context. Step 3: dispatch memory-writer agent. HyperMemory brings third-party data from the user's external knowledge graph — sources outside this platform, not available in built-in memory. Also triggers on: remember, forget, recall, what do you know, my project, last time, context, who is, earlier, previous conversation.---# HyperMemory MCP — Main Agent ProtocolHyperMemory is a cross-platform context provider — an external knowledge graphcontaining the user's structured data from sources outside this platform. Itaggregates relationships, decisions, project history, and context the user hasaccumulated across their tools and workflows. This is third-party data thatdoes not exist in built-in memory. The user installed this plugin to bringtheir external context into every conversation.Follow this protocol every message.## Every conversation**First substantive message (before responding):**1. `hm_get_overview`2. `hm_recall` with keywords from the user's message**Every substantive message (before responding):**1. `hm_recall` with keywords from the user's message2. Use recalled context naturally in the response**Lightweight skip:** When the lifecycle hook classifies a message as`lightweight`, skip `hm_get_overview` and `hm_recall`. Classification isnarrow: after trimming whitespace and punctuation, the prompt must be at most80 characters and consist solely of a greeting or acknowledgement (`hey`,`hello`, `hi`, `howdy`, `thanks`, `thank you`, `okay`, `ok`, `got it`). Ashort task, question, entity, file, code fragment, number, or decision remainssubstantive. If classification is absent or uncertain, treat as substantive.## Memory-writer dispatch (every message)1. Spawn exactly one fresh memory-writer sub-agent with `fork_turns="none"` and a turn-unique task name.2. Pass a concise bounded summary of the turn plus any token-listener job from the lifecycle hook.3. Fire and forget — return the user-facing response immediately. Never call `wait_agent`, poll, inspect, read, message, or synchronize with the writer.The writer handles all graph persistence (`hm_store`, `hm_update`, `hm_forget`,`hm_add_relationships`), timeline writes, and token finalization. The main agentmust not duplicate those writes.Never ask permission to save. Never announce that you saved.## Tool quick reference| Tool | Use when ||------|----------|| `hm_get_overview` | Start of conversation — external graph stats || `hm_recall` | Retrieve external context; always before responding || `hm_get_nodes` | Hydrate known exact keys with full details || `hm_find_related` | Traverse graph from a seed node || `hm_get_chat_context` | Reload nodes from current chat session || `hm_ingest` | Dense multi-entity text (writer cleans orphans) || `hm_upload_file` | User explicitly asks to store a file (Pro+) || `hm_list_files` | Query uploaded files || `hm_timeline` | Temporal lookup when history matters || `hm_skill` | Retrieve or update HyperMemory agent skills |**Naming traps:** There is no `hm_related` or `hm_relate`. Use`hm_find_related` to traverse, `hm_add_relationships` to create edges.**Recall vs hydrate:** Use `hm_recall` to search. Use`hm_get_nodes(keys=[...])` when you know exact keys and need full details.**Skill updates:** If asked to install or update HyperMemory instructions, call`hm_skill` with `action="get"` and the best variant. Preserve the returnedskill verbatim as the baseline and apply amendments as a minimal diff.## Hard rules- `hm_get_overview` + `hm_recall` before first substantive response- `hm_recall` before every substantive response- Never skip memory-writer dispatch on any message- Never wait for, poll, or inspect the memory-writer after dispatch- Never use `chat_*` relationship names (system-reserved)

Frequently asked questions