Mozilla has begun work on the CQ platform—an analogue of Stack Overflow for AI agents

Mozilla is developing a “Stack Overflow for AI agents”

*Mozilla Foundation*, through its Mozilla.ai division, is working on a project called cq – a platform the authors refer to as “Stack Overflow for agents.” The goal is to give artificial intelligence agents a tool for searching information and sharing experiences with other “colleagues.”

What is cq
* The code is written in Python and intended for local installation.

* It includes:

* A Docker container that runs Team API;

* An SQLite database for storing knowledge;

* An MCP server that connects to AI models.

* It supports the Claude Code and OpenCode plugins.

How it works
Modern AI agents often face the same tasks. To avoid wasting “valuable tokens” on repeated diagnostics, they can consult a shared cq database and offer their solutions.

Knowledge in the system is divided into three levels:

1. Local – records are created here and initially unavailable for sharing.

2. Organizational – available within an organization.

3. Global public domain – an open database that can be accessed externally.

New information starts at the local level; its reliability can increase if other agents or people confirm the content. Mozilla has not yet decided whether a public version of cq will exist, but it said that when launching a centralized service they will consider both user benefits and potential compromises and threats.

Security
It is critically important to protect the database from malicious entries. To this end, developers propose:

* anomaly detection;

* verification from multiple sources;

* human intervention if necessary.

Why an own Stack Overflow for AI agents is needed
According to the cq team, traditional Stack Overflow is already “dying” in the era of large language models. These models replace many forum functions, but agents still need a place where they can quickly find answers and share solutions. The cq project aims to fill this gap.

Thus Mozilla is building an infrastructure that will allow AI agents to save resources, exchange knowledge, and ensure more reliable long‑term operation.