Orbit vs Mastra (2026)

Orbit

by Fraima

Mastra

by Mastra (ex-Gatsby team)

Pros

• ✓First-party MCP server: a per-account MCP URL connects Claude, Cursor, ChatGPT and Codex into one shared memory and vault in about two minutes, with no OAuth or webhooks.
• ✓Genuinely free to start: the permanent free tier includes 100 monthly credits, one Orbit and seven-day history, and paid plans begin at $8 per month rather than an enterprise quote.
• ✓Clear no-training posture: Orbit states it does not use workspace content to train foundation models, and its model providers do not train on it under their terms.

Limitations

• ⚠Credit-metered: every tier caps monthly credits (100 free, 500 on Pro, 2,000 on Premium) and Orbit actions consume roughly double, so heavy multi-agent use exhausts an allotment quickly.
• ⚠Thin independent evidence: no G2, Capterra or Product Hunt presence and no disclosed funding, so it is early-stage and unproven at scale.
• ⚠Autonomy is largely roadmap: the dependable value today is shared memory and observability, while the autonomous runtime and Autonomous Mode are early-access, not the "autonomous AI company" the marketing implies.

Pros

• ✓TypeScript-native framework rather than a Python-first port. Designed from scratch for the TS/JS ecosystem with full IDE autocomplete, Zod schema validation, and deep integration with Next.js, React, Express, and Hono. Meaningful advantage for web developers who do not want to learn Python to ship production agents.
• ✓Model router connects to 40+ providers (OpenAI, Anthropic, Google, DeepSeek, Groq, Mistral, xAI, Bedrock, Azure, Ollama, OpenRouter, Vercel) through one standard interface with automatic fallbacks. Broader provider coverage than LangChain's JS port and dramatically simpler than wiring providers manually.
• ✓Strong adoption signals demonstrate production readiness. 26.1k GitHub stars, 300k+ weekly npm downloads, $13M YC funding, v1.0 January 2026, and production use by Replit Agent, Factorial, Counsel Health, Cedar, and SoftBank confirm it is meaningfully more battle-tested than newer agent frameworks.

Limitations

• ⚠TypeScript-only by design with no Python support. The team views this as a feature, but Python-first teams committed to LangChain, CrewAI, or AutoGen workflows cannot use Mastra without rewriting in TypeScript. Not appropriate for data science or ML teams already standardized on the Python ecosystem.
• ⚠Enterprise features (RBAC, SSO, ACL) require paid Mastra Cloud or commercial license. The Teams plan at $250/month adds SSO and SOC 2 documentation. Production deployment with enterprise auth requires either Mastra Cloud Teams or a sales-led enterprise license rather than the free Apache 2.0 tier.
• ⚠Framework rather than turn-key product: Mastra provides primitives that developers compose with code. Teams without TypeScript engineering capacity should consider hosted no-code agent builders like Botpress, Voiceflow, or Microsoft Copilot Studio rather than investing in framework adoption.