Agno vs Mastra
A side-by-side comparison of Agno and Mastra, two Orchestration tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Agno | Mastra |
|---|---|---|
| Category | Orchestration | Orchestration |
| Pricing (differs) | FREE | FREEMIUM |
| License (differs) | Open source | Open core |
| Deployment (differs) | — | Hybrid |
| Platforms | API, CLI | API, CLI |
| Model support (differs) | Model-agnostic | Multi-model |
| Vendor (differs) | Agno | Mastra |
| Capabilities (differs) |
|
|
The honest brief
Agno
Built for speed and scale — agents instantiate near-instantly with low memory, and ship to production via the bundled AgentOS FastAPI runtime.
- Fast agent instantiation, low memory use
- Multi-modal agents and agent teams
- Bundled AgentOS production runtime
- Model- and provider-agnostic
- Younger than LangChain and LlamaIndex
- Rapid changes since the Phidata rename
- Smaller community and ecosystem
Mastra
Built TypeScript-first on the Vercel AI SDK — far less boilerplate and faster runtime than LangGraph's abstractions.
- TypeScript-native, low boilerplate
- Graph workflow engine plus memory and tools
- Self-hostable or deploy to Mastra Cloud
- Built-in observability
- Younger ecosystem, fewer examples
- Small plugin set (~50-60 integrations)
- Workflow chaining unintuitive for complex branching
- TypeScript-only; no Python path
When to pick which
Both cover Agent framework, Multi-agent orchestration, Tool / function calling, and Agent memory.
Pick Agno if you need RAG pipeline and App / agent deployment.
- RAG pipeline (secondary capability)
- App / agent deployment (primary capability)
Pick Mastra if you need MCP server and LLM observability.
- MCP server (secondary capability)
- LLM observability (secondary capability)
Mastra leans on Agent framework as a headline capability; Agno treats it as secondary.
- Agent framework (primary capability)
They also differ on:
- Pricing
- FREE · FREEMIUM
- License
- Open source · Open core