# Mastra @mastra/core@1.79.0: what's new, verdict & setup

Canonical: https://theagenticweekly.com/tools/mastra · Released: 2026-10-21 · Last verified: 2026-10-25 · Evidence: Tested (smoke test, 2026-10-25, local 3B model (Qwen2.5-3B)) · Vendor: Mastra · Official site: https://mastra.ai/

> TypeScript framework for AI-powered applications and agents, with a local Studio.

## Verdict

**A strong TypeScript option if you are building agents in a Node stack; read the breaking-change note on sessions before upgrading.**

Good for:
- TypeScript and Next.js teams building agents
- Teams that need observability and tracing out of the box
- Developers experimenting with MCP events

Skip if:
- You work in Python
- You need a stable session API; this release changes it

Tested. Tested 2026-10-25 (America/Chicago). Mastra passed 5 of 5 on Node 20 (0.24.9) and 5 of 5 on Node 24 (1.79.0) with temperature pinned to 0, after failing 5 of 6 earlier trials at default sampling. Test environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key. Agent tools were pointed at a local open-weight model (Qwen2.5-3B-Instruct (Q4_K_M) through Ollama 0.40.11), so we tested the tool, not any vendor's hosted models. Not tested: Any vendor-hosted model: everything ran against one local 3B model; Multi-agent flows, memory, streaming and deployment; Anything beyond one tool and one question; five trials is a smoke test, not a benchmark. These are smoke tests, not a benchmark. Full log: /tests/mastra.

Test scope:
- Kind and date: smoke test, 2026-10-25 (America/Chicago). Not a benchmark.
- What we ran: Mastra passed 5 of 5 on Node 20 (0.24.9) and 5 of 5 on Node 24 (1.79.0) with temperature pinned to 0, after failing 5 of 6 earlier trials at default sampling.
- Model used: Qwen2.5-3B-Instruct (Q4_K_M) through Ollama 0.40.11
- Environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key
- Not tested: Any vendor-hosted model: everything ran against one local 3B model; Multi-agent flows, memory, streaming and deployment; Anything beyond one tool and one question; five trials is a smoke test, not a benchmark.

Full test log (commands, versions, raw output): [Mastra 0.24.9 (Node 20) / 1.79.0 (Node 24): our test log](https://theagenticweekly.com/tests/mastra)

Pricing: Not verified. We have not verified pricing for this tool; see the official site.

## Best for

- [Best AI tool for agent building](https://theagenticweekly.com/best/agent-building) (#6): TypeScript-first framework with Studio, observability and MCP support.

## What's new

@mastra/core 1.79.0 adds experimental MCP Events, richer observability (span aggregation and time-to-first-chunk), session-ID based agent controller sessions (a breaking change) and a native filesystem API for sandboxes.

- @mastra/core@1.79.0 (Oct 21): Experimental MCP Events let MCP servers publish event streams that clients can poll, stream or receive by signed webhook, with Studio inspection under mastra dev.
- Observability: new aggregateSpans() for per-span analytics such as p95 latency per tool, plus timeToFirstChunkMs fields and richer querySpans filters.
- Agent controller sessions are now addressed by sessionId, allowing many sessions per resource (breaking change).
- Sandboxes can expose a native filesystem API for faster file operations.
- @mastra/connect adds per-end-user connection scoping and a Microsoft Teams channel.

## How to set it up: Create a Mastra project

Steps come from the vendor's own docs or README. We ran Mastra on 2026-10-25; the test log lists what was and was not covered.

1. **Scaffold a project.** The README starts with the create command.

```
npm create mastra@latest
```
2. **Run the local Studio.** Mastra has a dev command that starts Studio so you can inspect agents. The release notes mention mastra dev for inspecting MCP events.

```
npx mastra dev
```
3. **Read the breaking changes.** Before upgrading an existing app to @mastra/core 1.79.0, read the release notes on controller sessions now keyed by sessionId.

## Pros and cons

Pros:
- TypeScript-native
- Detailed release notes with highlights
- Strong observability additions in this release

Cons:
- Breaking change to agent controller sessions in this release
- License reported as NOASSERTION on GitHub, so check the repository's license text
- Some features are experimental
- Our test was one small task on a local 3B model; it does not show behaviour with hosted models or larger jobs

## Alternatives

- [CrewAI](https://theagenticweekly.com/tools/crewai): Python framework for orchestrating role-playing, autonomous AI agents that work as a crew.
- [LangGraph](https://theagenticweekly.com/tools/langgraph): Low-level framework for building long-running, stateful agents as graphs.
- [OpenAI Agents SDK](https://theagenticweekly.com/tools/openai-agents-sdk): Lightweight Python framework for multi-agent workflows, with tools, handoffs, sessions and tracing.
- [Langflow](https://theagenticweekly.com/tools/langflow): MIT-licensed visual builder for AI agents and MCP servers with a very large GitHub following.
- [Botpress](https://theagenticweekly.com/tools/botpress): Customer-support AI agent platform with a free plan and conversation-based paid plans.
- [Gumloop](https://theagenticweekly.com/tools/gumloop): Agent builder for teams; plans start at $37 per month with 20k included credits.
- [Lindy](https://theagenticweekly.com/tools/lindy): AI 'employee' builder that connects to your tools; Free plan with $50 in credits that last 7 days, then credit-based plans.
- [Microsoft Copilot Studio](https://theagenticweekly.com/tools/copilot-studio): Microsoft's platform for creating and managing custom agents, workflows and apps with no code.
- [Pydantic AI](https://theagenticweekly.com/tools/pydantic-ai): Python agent framework built on Pydantic types, covering agents, realtime voice, image generation and embeddings.
- [Relevance AI](https://theagenticweekly.com/tools/relevance-ai): Platform for specialist AI agents for sales, customer success, marketing and HR, with an embedded deployment team.
- [Voiceflow](https://theagenticweekly.com/tools/voiceflow): Platform for chat and voice AI agents for customer experience teams.
- [Vercel AI SDK](https://theagenticweekly.com/tools/vercel-ai-sdk): Vercel's TypeScript SDK that gives one API across many model providers, with streaming and agent helpers.

## FAQ

### What is new in Mastra @mastra/core 1.79.0?

Experimental MCP Events, span aggregation and time-to-first-chunk observability, session-ID based controller sessions (breaking), a native sandbox filesystem API, and per-user connection scoping in @mastra/connect.

### How do I start a Mastra project?

Run npm create mastra@latest.

### Is Mastra open source?

The code is public on GitHub; GitHub reports the license as unspecified, so read the repository's license file before using it commercially.

## What we have not verified

- License terms (GitHub reports NOASSERTION)

## Sources

- [@mastra/core@1.79.0 release](https://github.com/mastra-ai/mastra/releases/tag/%40mastra/core%401.79.0) (fetched 2026-10-25)
- [README](https://github.com/mastra-ai/mastra) (fetched 2026-10-25)

## How to cite

Agentic Weekly, "Mastra @mastra/core@1.79.0: what's new, verdict & setup", last updated 2026-10-25, https://theagenticweekly.com/tools/mastra

Keep the Reported or Tested label when you quote the verdict.