What is oqoqo?
Oqoqo is an evaluation platform designed for testing AI agents on real-world software tasks. It provides managed cloud infrastructure to run automated experiments at scale, allowing teams to build private benchmarks and evaluate how effectively agents interact with tools and developer products. By executing trials across different models, agents, and tool configurations, the platform tracks task success rates, records tool execution, and identifies interface frictions and token inefficiencies.
oqoqo key features
- Runs agent trials on isolated, sandboxed virtual machines configured with specific repositories, files, dependencies, and environment states.
- Compares tool packages and treatments, such as Model Context Protocol (MCP) servers, CLIs, skills, APIs, and SDKs, against baseline setups.
- Evaluates multiple agents and models, including Claude Code, Codex, Cursor, GitHub Copilot, and OpenCode, utilizing bring-your-own model credentials.
- Captures complete execution trajectories, recording terminal commands, tool calls, error logs, token metrics, and failure points.
- Provides access across a web application, command-line interface (CLI), and MCP servers to trigger experiments manually, programmatically, or via CI pipelines.
Who is oqoqo for?
Oqoqo is intended for software engineers, product teams, and AI developers who build agent-facing tools or need to evaluate autonomous agent performance. Typical use cases include testing whether agents can successfully use developer products like SDKs or MCP servers, comparing different agent-model combinations on domain-specific tasks, analyzing where agents get stuck during execution, and running automated regression evaluations when updating software interfaces.