Supermemory remembers what you told it.
memco remembers what your agents learned.

01The difference

• What it remembers

  Supermemory

  User context, documents and maintained profiles.

  memco

  What agents learned doing the work.

• What improves over time

  Supermemory

  Facts about each user, updated as things change.

  memco

  Behavior on the next task, measured.

• Who learns from whom

  Supermemory

  Memory is isolated per container: a user, project or organization.

  memco

  Everyone in the network; personal preferences stay in personal memory.

02Honest overlap

Where the products genuinely overlap.

1. Both persist and retrieve memory for agents.
2. Both offer a developer API.
3. Both can be used by individuals through MCP and plugins.
4. Both are model-agnostic.

03Where each product starts

Different centers of gravity.

• Supermemory · User memory API

  Give an agent a standing memory of each user, task or tenant.

  • Primary inputs: conversations, files, URLs and synced sources such as Drive, Gmail, Notion and GitHub.
  • Outcome: a maintained profile and searchable facts in the agent’s context.

• memco · Trusted insight

  Convert real agent work into trusted, scoped and reusable team insights.

  • Primary inputs: agent work, corrections, decisions and outcomes.
  • Outcome: a later task goes better, for another person, session or tool.

04The same week, replayed

One payment-retry bug. Two product jobs.

Illustrative engineering workflow; not customer evidence. The same scenario runs on every comparison page, so what differs is the product job, not the anecdote.

1. Agent A · Cursorpayment-retry taskcalls a helper that was retired last quarter
2. Failed testci · redthe dead end costs the run its first hour
3. Senior correctionreview + passing PRthe durable fact: which path works now, and why
4. Scoped trusted insightteam scope · provenance keptsource, contributor, scope and outcome attached
5. Agent B · Claude Codenext week · different personstarts ahead of the dead end

• What they can represent

  Supermemory could store the correction as a fact in a shared project container, which a second agent can search if it is scoped to the same container.

• What memco makes of it

  memco makes the source, trust state, team scope and later outcome the primary object, then tests whether another engineer's agent avoided the failed path.

05Practical comparison

Dimension by dimension, in words.

Rows, not scoreboards: each dimension states what each product actually does, so the difference survives scrutiny.

Scroll sideways →

06Choose honestly

Two good answers to two different questions.

• Choose Supermemory if

  • You want an assistant that knows its user across sessions and sources.
  • User memory plus document retrieval is the main job.
  • One person, or one product’s users each on their own.

• Choose memco if

  • An insight from one person's agent should improve a later task for another person or tool.
  • Corrections, failed paths and accepted outcomes keep getting rediscovered.
  • Shared learning needs source, standing, governance and a path to correction or retirement.
  • The learning should survive model, IDE and agent-platform changes.

07For your customers

If you are building memory into a product

• Supermemory SDK

  A memory API per end user, with profiles and document ingestion.

• memco SDK

  A memory network per customer, learning from their agents’ work, seeded from yours, metered by use.

  Build with the memco SDK →

08Proof, not vibes

The reuse test.

Do not stop at 'the agent remembered.' If the main job is an assistant that knows its user across sessions and sources, evaluate Supermemory. If the job is to make real engineering learning travel across people and tools, run the reuse test.

1. Pick one repository and one repeated failure, correction or convention.
2. Record the baseline behavior without the shared insight.
3. Let Agent A hit the problem and capture the source-backed correction.
4. Review and scope the candidate insight using the product states actually available.
5. Give Agent B a related task in another session or tool.
6. Measure repeated-error rate, completion, agent steps, review corrections and source/scope integrity.
7. Record whether the insight helped, conflicted or should be corrected or retired.

A signup is not activation. Activation is an insight contributed from one task and correctly reused on a later task.

Run the reuse test →Read the research →

09Questions

What evaluating teams ask.