mastra vs copilotkit
Two of the top projects in Agent frameworks and SDKs, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
mastra
TypeScript framework for building AI agents, workflows and MCP servers
copilotkit
React and Angular SDK for adding agent chat and generative UI to apps
Verdict
mastra ranks higher, 92 to 90. Of the 4 score parts we measure for both, mastra leads on 2, copilotkit on 1 and 1 is even.
- Adoptioncopilotkit leads by 5 points, 89 to 84.
- FreshnessEven at 100.
- Maintenancemastra leads by 6 points, 94 to 88.
- Agent-readymastra leads by 15 points, 85 to 70: a wide gap.
Pick mastra if you are
TypeScript developers building production agents and workflows
- Graph workflow engine with .then(), .branch() and .parallel() control flow
- Suspend and resume agents or workflows, with execution state kept in storage
Pick copilotkit if you are
Frontend and full-stack teams shipping agent UIs inside their own products
- Works with many agent backends: LangGraph, CrewAI, Mastra, Google ADK, PydanticAI, Strands, LlamaIndex
- Covers React, Angular, Vue, React Native, plus Slack and Teams channels
| What we compare | mastra | copilotkit |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 84, widely used | 89, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 94, healthy | 88, healthy |
| Agent-ready | 85, ready | 70, partly |
| Facts from GitHub and the README | ||
| Stars | 29.5k | 38.7k |
| License | custom license (read the license) | MIT (permissive) |
| Last commit | Nov 2026 | Nov 2026 |
| Last release | Nov 2026 | Nov 2026 |
| Language | TypeScript | TypeScript |
| Docker | No | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
mastra
Mastra is a TypeScript framework for building agents and graph-based workflows, with model routing across 40+ providers. It adds suspend/resume with stored state, memory, RAG, evals and observability, and runs inside React, Next.js or Node apps or as a standalone server. A local Studio on port 4111 is used to build and test agents, workflows and tools.
Who it is for: TypeScript developers building production agents and workflows
Strengths
- Graph workflow engine with .then(), .branch() and .parallel() control flow
- Suspend and resume agents or workflows, with execution state kept in storage
- Built-in evals, observability, memory and RAG alongside agents
- Can author MCP servers exposing agents and tools
Weaknesses
- TypeScript only; no other language SDKs mentioned
- Code in ee/ directories needs an enterprise license for production use
- Pull requests limited to collaborators
- No Docker or compose files in the repo
- no GPU
- Needs Node.js, LLM provider API key
- Models: OpenAI, Anthropic, Gemini, xAI, 40+ providers via model router
- port 4111
copilotkit
CopilotKit is a TypeScript SDK and runtime that connects an existing agent (LangGraph, CrewAI, Mastra, Google ADK, PydanticAI and others) to a frontend over the AG-UI protocol. It provides chat components, generative UI, shared agent/UI state, human-in-the-loop approvals and frontend tools for React, Angular, Vue, React Native, Slack and Teams. A separate Intelligence layer adds memory, thread persistence and Continual Learning.
Who it is for: Frontend and full-stack teams shipping agent UIs inside their own products
Strengths
- Works with many agent backends: LangGraph, CrewAI, Mastra, Google ADK, PydanticAI, Strands, LlamaIndex
- Covers React, Angular, Vue, React Native, plus Slack and Teams channels
- Three generative UI modes: registered components, A2UI specs, sandboxed MCP Apps
- Hooks such as useAgent give programmatic control beneath the prebuilt chat components
Weaknesses
- Memory, persistent threads and Continual Learning sit in Intelligence, not the MIT SDK
- Slack and Teams are GA only on cloud-hosted Intelligence
- Needs a separately built agent or the built-in agent plus an LLM API key
- Angular, Vue and React Native are listed as supported, while React/Next.js is the GA surface
- no GPU
- Needs Node.js/npm, LLM provider API key (e.g. OpenAI)
- Models: OpenAI (built-in agent), LangGraph, CrewAI, Mastra, Google ADK
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