ReMe vs cq
Persistent AI agent memory compared
ReMe and cq help AI agents reuse information across sessions. ReMe organizes conversations and resources into editable Markdown memory, while cq focuses on structured, reviewed lessons for coding agents.
ReMe: Build a File-Based Memory Workspace for AI Agents
ReMe is a Python memory-management kit for agents, built around a local-first, self-evolving knowledge base stored as Markdown files. It helps agent users capture conversations and resources, refine durable knowledge, and retrieve relevant context across supported agent integrations.
cq: Share Collective Learning Between AI Agents
cq is a knowledge store and workflow for coding agents to query, contribute, and validate reusable lessons. It helps teams and individual developers avoid repeating debugging work across agent sessions and machines.
| ReMe | cq | |
|---|---|---|
| Language | Python | Go |
| License | Apache-2.0 | Apache-2.0 |
| Stars | 3.7k | 1.3k |
| Forks | 321 | 69 |
| Last analyzed | Oct 23, 2026 | Oct 3, 2026 |
Key differences
- ReMe stores memories as Markdown files with frontmatter and wikilinks; cq organizes reusable guidance as structured knowledge units.
- ReMe supports general agent memory workflows, including conversation capture and resource imports; cq is oriented toward coding lessons, debugging, and workarounds.
- ReMe is written in Python and provides CLI, HTTP, MCP, and Python interfaces; cq is written in Go and provides MCP tools, a CLI, and Go and Python SDKs.
- ReMe defaults to a local service and workspace; cq supports local SQLite storage, Mozilla.ai's hosted service, or a self-hosted server.
- ReMe offers optional semantic retrieval through embeddings; cq provides workflows for proposing, confirming, and reviewing knowledge.
- cq is a 0.x project and warns that breaking changes are expected; ReMe's provided project facts do not list a comparable maturity warning.
Choose ReMe if you…
- want persistent, editable Markdown memory for an agent across sessions.
- need to capture conversations and reference resources, then retrieve linked or searchable passages.
- want interfaces such as HTTP or Python alongside CLI and MCP access.
Choose cq if you…
- need coding agents to reuse structured lessons about errors, APIs, or workarounds.
- want agents to query and propose knowledge that people can review before sharing.
- need a choice of local storage, hosted service, or self-hosted server for a shared knowledge store.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.