aimock (CopilotKit/aimock) is an open-source AI project on GitHub. Repository summary: Mock everything your AI app talks to — LLM APIs, MCP, A2A, AG-UI, vector DBs, search. One package, one port, zero dependencies. Its focus includes MCP and tool-calling integration, retrieval-augmented generation. It is suitable for extension, integration, and iterative delivery in real workflows.
License
MIT
Stars
569
Homepage
http://aimock.copilotkit.dev/Features
- Core capability: Mock everything your AI app talks to — LLM APIs, MCP, A2A, AG-UI, vector DBs, search. One package, one port, zero dependencies.
- Provides MCP or tool-calling integration
- Supports vector retrieval and retrieval-augmented reasoning
- Repository: CopilotKit/aimock
- Primary language: TypeScript
- Open-source license: MIT
Use Cases
- Connects external systems into agent workflows
- Builds enterprise knowledge Q&A and document retrieval systems
- Build internal AI workflow prototypes with aimock
- Validate aimock in production-like engineering scenarios
- Building AI development workflows
- Automating agent-based processes
FAQ
Teams should first define integration boundaries and call patterns, then map repository capabilities into concrete interfaces, parameters, and access rules. GitHub repository: https://github.com/CopilotKit/aimock. Community traction is around 569 stars. License: MIT.
It usually works as an execution component or capability layer, with common deployment fits such as: Connects external systems into agent workflows, Builds enterprise knowledge Q&A and document retrieval systems, Build internal AI workflow prototypes with aimock.
