Lindy.ai vs Mastra
Side-by-side comparison of two agent options that often come up together when people are choosing between self-hosted frameworks, managed assistants, and extensible AI tooling.
Closed sourceN/A stars
Lindy.ai
Enterprise productivity assistant with 4,000+ integrations
Open source23k stars
Mastra
TypeScript-first agent framework with observational memory and workflow orchestration
Category
Lindy.ai
Mastra
Tagline
Enterprise productivity assistant with 4,000+ integrations
TypeScript-first agent framework with observational memory and workflow orchestration
Deployment
Managed SaaS
Self-Hosted
Pricing
Mid-tier paid pricing that fits regular professional use better than hobby use.
Free to use, with optional model or infrastructure costs if you self-host.
Channels
iMessage, SMS, Email, Web
Web, CLI
Open source
No
Yes
Privacy
Some privacy controls exist, but vendor-hosted infrastructure still handles a meaningful share of the data flow.
Good privacy posture for most teams, especially when self-hosted or carefully configured.
Lindy.ai pros
- Security posture is strong for sensitive workflows.
- Extensible enough for custom tools, plugins, or workflow glue.
- Good memory and persistence support for ongoing conversations or tasks.
Mastra pros
- TypeScript-first — rare in the agent framework space (most are Python)
- Observational Memory — automatically tracks and surfaces agent reasoning patterns
- From the Gatsby team — proven track record building developer-facing OSS
Lindy.ai cons
- No modern chat apps (no Telegram, WhatsApp, Discord, Slack)
- Lower privacy score — data processed on their servers
- Closed source with mid-tier pricing
Mastra cons
- TypeScript-only — not suitable for Python-heavy stacks
- Younger ecosystem compared to LangChain or CrewAI
- Primarily a development framework — not a ready-to-use personal assistant
Lindy.ai gotchas
- Recurring subscription or model spend can matter more than the headline feature list.
Mastra gotchas
- You should expect ongoing hosting, uptime, and secret-management work if you deploy it for real users.
Not sure which one fits you?
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