CopilotKit/aimock
Mock everything your AI app talks to — LLM APIs, MCP, A2A, AG-UI, vector DBs, search. One package, one port, zero dependencies.
- Stars
- 985
- Forks
- 81
- Open issues
- 4
- Last push
- today
About aimock
aimock is a free, open-source AI developer tool by CopilotKit, written mainly in TypeScript. Mock everything your AI app talks to — LLM APIs, MCP, A2A, AG-UI, vector DBs, search. One package, one port, zero dependencies. It has 985 GitHub stars and 81 forks, and was last updated today. It's released under the MIT license, a standard open-source license.
- License
- MIT
- Language
- TypeScript
- Stars
- 985
- Last update
- today
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not required
- Self-hostable
- Yes
Similar free tools
litellm62k stars · The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, load balancing, and logging [Bedrock, Azure, OpenAI, Anthropi
mcp-use11k stars · The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.
langchain148k stars · The agent engineering platform.
RagaAI-Catalyst16k stars · Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced anal
openai-cookbook77k stars · Examples and guides for using the OpenAI API
giskard-oss5.9k stars · 🐢 Open-Source Evaluation & Testing library for LLM Agents
aimock FAQ
Is aimock free?
Yes. aimock is open source and free to use. It's released under the MIT license, a standard open-source license.
Does aimock run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does aimock need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is aimock still maintained?
Yes. It was last updated today and has 4 open issues on GitHub.
What are alternatives to aimock?
Similar free, open-source tools include litellm, mcp-use, langchain, RagaAI-Catalyst.