· 1 observation
Technical updates · 1
Package or technical metadata updated
View technical comparison →Empirical v1.3.5
Memory across your AI tools
From the developer
The MCP tools do not purchase products, transfer funds or process payments. Empirical account subscriptions are managed on the Empirical website.
Recall relevant context for this project.
Developer declarations; not independently tested. Listing last checked Nov 8, 2026. Package observed Nov 7, 2026.
From the marketplace listing
Empirical keeps your memories, preferences and project decisions available across ChatGPT, Codex and other connected AI tools. Save context you want to remember, find it later, and update it as your plans change. Organize personal and shared context into workspaces, and explore connections between memories. Requires an Empirical account and an authenticated connection. Access is limited to workspaces available to your connected account. Memory search can return partial matches; inspect the sources before relying on a result. Empirical stores and processes the memory content you choose to save. Do not store passwords, API keys or other secrets.
Language: English · Automatically detected from descriptions.
Exact text from the indicated source. A mention alone does not establish support for your task.
app-699db5f04b788191a4f9ee070d3e5d67
Recall and save your memories, preferences and project decisions across ChatGPT, Codex and other connected AI tools with Empirical.
Empirical keeps your memories, preferences and project decisions available across ChatGPT, Codex and other connected AI tools. Save context you want to remember, find it later, and update it as your plans change. Organize personal and shared context into workspaces, and explore connections between memories. Requires an Empirical account and an authenticated connection. Access is limited to workspaces available to your connected account. Memory search can return partial matches; inspect the sources before relying on a result. Empirical stores and processes the memory content you choose to save. Do not store passwords, API keys or other secrets.
· 1 observation
Package or technical metadata updated
View technical comparison →· 4 observations
Full description changed from “Cross-project personal memory through Empirical CLI and MCP. Use for research, debugging, specs, status, handoffs, personal context, lead/CRM work, assistant...” to “Use Empirical to recall/save durable project context across sessions and projects, and to look up how to use Empirical...
View comparison →Plugin name changed from “Empirical” to “Empirical Memory”. Is template instance added: “false”. App-699db5f04b788191a4f9ee070d3e5d67 updated; open the comparison for details. Empirical updated; open the comparison for details. 16 more changes in the comparison.
View comparison →Plugin name changed from “Empirical” to “Empirical Memory”. Is template instance added: “false”. App-699db5f04b788191a4f9ee070d3e5d67 updated; open the comparison for details. Empirical updated; open the comparison for details. 15 more changes in the comparison.
View comparison →Package or technical metadata updated
View technical comparison →Find competitors to follow as you develop your plugin.
Esment gives ChatGPT persistent, inspectable memory for facts, preferences, decisions, and project context. It can recall relevant contex...
Shared terms: memory, preference, recall, decision
Kumiho Memory saves the decisions, facts, preferences, and reasons you choose to keep in your connected Kumiho workspace, then retrieves ...
Shared terms: remember, decision, context, later
MemStore saves information you choose to remember and retrieves it in later conversations with source references. Load saved context, sea...
Shared terms: memorie, recall, save, later
Consent-first persistent memory for your Kemory vault.
Shared terms: memory, decision, context, save
Save facts, preferences, and project details to a MemoryPlugin account and recall them in later ChatGPT conversations. What it does: - S...
Shared terms: memorie, recall, save, later
---
name: empirical-memory
description: Use Empirical to recall/save durable project context across sessions and projects, and to look up how to use Empirical itself - CLI commands, install/auth/workspace/kit/skill setup, docs.
---
# Empirical Memory (MCP mode)
Use Empirical to carry durable context across projects and clients, and as the first stop for
"how do I use Empirical" questions — command syntax, install/auth/workspace/kit/skill setup, or
what Empirical can do. Don't answer those from general knowledge or by guessing: use the
`memory_usage_guide` MCP tool for the current, agent-readable answer first.
This variant is for installs where the user chose MCP as their integration mode. The connected
Empirical MCP server is the primary and expected way to reach Empirical here — use its tools
directly, not `empirical` CLI commands, as the first move.
**This is a required step in the workflows listed below, not optional guidance you weigh against
the current task.** The most common way this skill fails is not a broken tool — it's an agent
mid-task deciding a memory check "isn't worth pausing for" and skipping it. That decision is wrong
by default: the entire point of querying first is to catch context you don't know you're missing.
If you are not sure whether a task qualifies, treat it as if it does.
## Before doing work — MUST, not discretionary
1. Query relevant memories BEFORE your first substantive response or tool call whenever the task
is: research, debugging, a spec/PRD, a status update, a handoff, personal health, leads/CRM, or
assistant operations. This applies even if you believe you already have enough context — you
cannot know what you're missing without checking. Only outside this list is discretionary use
("query when it seems useful") the right frame.
2. If you have not used Empirical's MCP tools yet this session, call `memory_usage_guide` once to
confirm current tool names, filters, and pagination behavior before relying on memory.
3. Use the `query_memories` MCP tool for recall. Use filters such as `category`, `tags`,
`nodeType`, and `monthKey` when they improve recall. For "recent/latest/today" requests, prefer
`list_memories` instead — it is the tool built for that shape of request. For exhaustive topic
retrieval, use the topic as a tag and follow pagination.
4. A slow response alone is API latency, not an outage; report an outage only when a tool call
returns an actual error, and use `get_empirical_policy` or a retry to verify connectivity before
escalating.
5. A filtered `query_memories` call (`category`, `tags`, `nodeType`) that returns nothing is not
proof the memory doesn't exist — it only proves nothing matched that exact filter combination.
A memory's real category or tag convention often does not match how you or the user would
naturally describe it in conversation (e.g. described as "an idea" but stored under a
different category; tagged with a project's short name where you tried its full one). Before
concluding a memory doesn't exist, retry at least once with the filter relaxed or removed —
category dropped, tags loosened to an OR match, or a plain unfiltered query — rather than only
varying the search phrase.
6. If a specific recall miss turns out to have a narrow, demonstrable cause (a filter mismatch, a
stale tag, a wrong category), stop there. Report that cause and move on — do not generalize one
miss into a theory about the memory system being broken and then go build measurement or
debugging work around the theory. Confirm the narrow cause is insufficient before entertaining a
systemic explanation, not after.
## Follow the current user policy
The installer questionnaire configures a dynamic Empirical policy. It is user-scoped and may
change without reinstalling this plugin. Read it when the skill activates:
1. Use the read-only `get_empirical_policy` MCP tool.
2. If policy lookup fails, use safe defaults: preserve durablPreview of the first 4,000 characters. Read full instructions →
Core memory skill and authenticated remote MCP connection packaged for ChatGPT and Codex. Includes listing links, Empirical brand assets and repeatable synthetic review cases. Optional workflow plugins remain separate.
Declared in the saved package. Remote tools may change independently.
Publisher declarations from the archived package. These are separate from our research and the live service's terms.
Package observed Nov 7, 2026.
plugin_asdk_app_699db5f04b788191a4f9ee070d3e5d67
Download plugin data (JSON)Plugin details: served from cache. Prepared . Refreshed when plugin data changes or after 6 hours. Your account and Follow status are live.