Mastra vs Oi: Which is Better in 2026?
A comprehensive comparison of Mastra and Oi covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Mastra if:
- →You need a broader feature set (6 features vs 5)
- →You need agents, tools, and workflows as typescript primitives or built-in observability: traces, metrics, and logs
Choose Oi if:
- →You want more affordable paid plans (from $19/mo)
- →You need contexts, guardrails, connections and workflows as reusable objects rather than saved prompts or connected once over mcp and available in codex, chatgpt, claude, openclaw and cursor
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Mastra vs Oi: At a Glance
Pricing Comparison: Mastra vs Oi
Understanding the pricing differences between Mastra and Oi is crucial for making the right choice. Here's how their plans compare side by side.
Mastra Pricing
💡 Pricing takeaway: Both Mastra and Oi offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Mastra and Oi stacks up.
What Makes Each Tool Unique
🔵 Unique to Mastra
Features available in Mastra but not in Oi:
- ✓Agents, tools, and workflows as TypeScript primitives
- ✓Built-in observability: traces, metrics, and logs
- ✓Evals, experiments, scorers, and datasets
- ✓Studio for collaborative iteration on agents
- ✓Server product for cloud deployment
- ✓Extensive learning material — course, books, templates, workshops
🟣 Unique to Oi
Features available in Oi but not in Mastra:
- ✓Contexts, Guardrails, Connections and Workflows as reusable objects rather than saved prompts
- ✓Connected once over MCP and available in Codex, ChatGPT, Claude, OpenClaw and Cursor
- ✓Public library of 1,000+ contexts, searchable and installable, with publishing on every tier
- ✓Guardrails that block outputs contradicting a rule, checked against systems of record
- ✓Industry solution kits for construction, real estate, property management and more
Use Case Recommendations
Best for: Mastra
Mastra is a TypeScript framework for building AI agents and the applications around them, built by the team that previously created Gatsby. The core framework covers agents, tools, and workflows as first-class primitives, so a long-running agent is expressed in ordinary TypeScript rather than assembled from prompt strings and glue code. Around that framework sits a platform: observability with metrics, logs, and traces so agent runs are inspectable after the fact; evals, experiments, scorers, and datasets for measuring whether a change actually improved behavior; a Studio for collaborating on and iterating over agents; an Agent Builder; and a Server product that handles cloud deployment for agents. The company emphasizes agents that run for days rather than single-turn calls, which is what pushes the observability and scoring surface to the center of the product instead of leaving it as an add-on. Mastra is open source with roughly 26.7k GitHub stars and maintains a substantial learning surface — a quickstart, project templates, a video course, two books (Principles of Building AI Agents and Patterns of Building AI Agents), live workshops, and a weekly podcast — which makes it one of the more approachable entry points for JavaScript developers moving into agent work.
Ideal use cases:
- •Teams or individuals who need agents, tools, and workflows as typescript primitives
- •Teams or individuals who need built-in observability: traces, metrics, and logs
- •Teams or individuals who need evals, experiments, scorers, and datasets
- •Teams or individuals who need studio for collaborative iteration on agents
- •Anyone focused on typescript workflows
- •Anyone focused on agent framework workflows
Best for: Oi
Oi is a shared operating layer that gives every AI tool in an organisation the same memory, workflows and guardrails, connected once through MCP and then available anywhere people work — the site names Codex, ChatGPT, Claude, OpenClaw and Cursor as clients. The unit of reuse is deliberately not the prompt. Four object types make up the library: Contexts, which carry a domain's working knowledge; Guardrails, which block outputs that violate a rule; Connections, which reach systems of record; and Workflows, which chain the rest into a repeatable procedure. The published examples are unusually concrete for this category and give a real sense of the depth on offer — a contract-administration Context that reads Procore RFIs and the drawing register to catch when work is a variation and drafts the claim with MYOB cost backup, a WHS Compliance Guardrail that blocks advice contradicting current Australian workplace-safety regulation by cross-referencing induction and SWMS records, a Progress Claim Pipeline Workflow that pulls percentage complete by cost code and reconciles it against committed and actual costs. Solution kits are packaged by industry, covering construction, real estate, property management, car dealers, fitness and fashion. A public library of over a thousand contexts is searchable and installable, and you can publish your own back to it from any tier including free. The meters to watch are agent messages, which are tight at 10 a day on free and 25 a day on Pro, and Connections, of which free has none.
Ideal use cases:
- •Teams or individuals who need contexts, guardrails, connections and workflows as reusable objects rather than saved prompts
- •Teams or individuals who need connected once over mcp and available in codex, chatgpt, claude, openclaw and cursor
- •Teams or individuals who need public library of 1,000+ contexts, searchable and installable, with publishing on every tier
- •Teams or individuals who need guardrails that block outputs contradicting a rule, checked against systems of record
- •Anyone focused on mcp-server workflows
- •Anyone focused on ai-governance workflows
🤖 Other AI Agent Infrastructure Tools to Consider
Mastra and Oi aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
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Frequently Asked Questions
Is Mastra better than Oi?
It depends on your needs. Mastra offers 6 key features including Agents, tools, and workflows as TypeScript primitives and Built-in observability: traces, metrics, and logs, while Oi provides 5 features including Contexts, Guardrails, Connections and Workflows as reusable objects rather than saved prompts and Connected once over MCP and available in Codex, ChatGPT, Claude, OpenClaw and Cursor. Mastra uses a freemium model with a free tier, while Oi is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is Mastra cheaper than Oi?
Both tools are similarly priced, starting at The framework is open source and free. Hosted platform tiers exist on the pricing page but the tier table is rendered client-side and not readable from a plain fetch, so no figure is quoted here.. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Mastra and Oi together?
Yes, many users combine Mastra and Oi in their workflow. Mastra excels at agents, tools, and workflows as typescript primitives, while Oi shines with contexts, guardrails, connections and workflows as reusable objects rather than saved prompts. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Mastra and Oi?
While both are ai agent infrastructure tools, Mastra emphasizes agents, tools, and workflows as typescript primitives, whereas Oi is known for contexts, guardrails, connections and workflows as reusable objects rather than saved prompts. The best choice depends on your specific workflow and feature priorities.
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