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Mastra Release Notes

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Mastra

Mastra 1.51.0: Wiederherstellung verwaister Durable-Agent-Runs, Platform-Workspace

Mastra 1.51.0 ermöglicht die Wiederherstellung verwaister Durable-Agent-Runs nach einem Neustart, erlaubt parallele AgentController-Sessions pro Scope, ergänzt mit @mastra/platform-workspace@0.1.0 Workspace- und Sandbox-Provider für die Mastra Platform und macht das Mastra Code SDK öffentlich und erweiterbarer.

Highlights

Durable Agent Crash Recovery (server + client + boot-time)

Durable agents can now discover and recover orphaned RUNNING runs after a restart via DurableAgent.listActiveRuns(), recover(), and recoverActiveRuns(), plus Mastra.recoverAllDurableAgents() and an opt-in MastraConfig.recovery: { durableAgents: 'auto' } for boot-time recovery. There’s also a standard HTTP/client surface (POST /agents/:agentId/recover + client-js agent.recover({ runId })) to reattach and stream the remaining output from dashboards or admin tools.

Scoped AgentController Sessions (parallel sessions per resource)

AgentController sessions now support a scope/sessionScope, allowing multiple independent sessions to run in parallel over the same resourceId (e.g., one per git worktree) without sharing run loops, threads, or state. The scope is also exposed in request context for integrations, and controller APIs now report run activity (running + per-thread state) for better UIs.

New Workspace + Sandbox Providers for Mastra Platform

A new package, @mastra/platform-workspace@0.1.0, adds PlatformFilesystem and PlatformSandbox providers that connect agents to Mastra Platform sandboxes and bucket-backed filesystems via the workspace-proxy API. This enables running workspace-dependent tooling against Platform-managed infrastructure with env-var or config-based setup.

Mastra Code SDK Now Public + More Extensible Integrations …

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Mastra

Mastra 1.50.0: LiveKit-Sprachagenten und einheitliche Schedules-API

Mastra 1.50.0 bringt mit @mastra/livekit Realtime-Sprachagenten über LiveKit, dateisystembasierte Registrierung von Mastra-Primitives (inklusive automatischer Mastra-Instanz ohne index.ts), eine vereinheitlichte Schedules-API unter mastra.schedules und /api/schedules, die die Heartbeats ersetzt, sowie eine Workspace-Provider-Registry im MastraEditor.

Highlights

LiveKit Realtime Voice Agents (@mastra/livekit)

New @mastra/livekit package turns Mastra agents (or per-turn workflows) into realtime voice agents with LiveKit handling the full audio loop (WebRTC, VAD, STT/TTS, turn detection, barge-in) while Mastra drives replies, tools, and memory—plus built-in tracing and a Studio “voice mode”.

File-System Routed Mastra Primitives + Zero-Boilerplate Startup

Mastra can now auto-discover and register storage.ts, observability.ts, server.ts, studio.ts, workflows/*.ts, and agent processors from the src/mastra directory during mastra dev/mastra build; @mastra/deployer can also auto-construct a Mastra instance when src/mastra/index.ts is missing, enabling fully file-based projects with no new Mastra(...) entry file.

Unified Schedules API (Heartbeats → Schedules)

Agent “heartbeats” and workflow schedules are unified under mastra.schedules and /api/schedules (client + server), with deprecated/removed heartbeat routes and methods; persisted legacy rows are normalized (target.type: 'heartbeat' → 'agent') so existing schedules keep firing across supported stores.

Workspace Provider Registry in MastraEditor …

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Mastra

Mastra 1.49.0: Aufbewahrungsrichtlinien, Mandantentrennung und scoreTrace()

Mastra 1.49.0 führt optionale Aufbewahrungsrichtlinien mit storage.prune() für Core sowie Postgres, libSQL und MongoDB ein, ergänzt optionale Mandantentrennung (organizationId/projectId) für Datasets, Experiments, Scores und Scorer und bietet mit scoreTrace() und scoreTraceBatch() das nachträgliche Bewerten gespeicherter Traces samt Score-Herkunft.

Highlights

Opt-in Storage Retention + storage.prune() (Core + Postgres/libSQL/MongoDB)

Mastra now supports per-domain/per-table retention policies (retention: { ...maxAge }) and a safe, batched, resumable storage.prune() to delete aged data across major “growth” tables (memory, observability spans, workflow snapshots, background tasks, experiments, schedules, etc.). Postgres/libSQL/MongoDB adapters add first-class pruning implementations (including partition/chunk drops for v-next observability in Postgres).

Multi-tenant Isolation for Datasets, Experiments, Scores, and Scorers

End-to-end optional organizationId/projectId scoping was added across dataset and experiment reads/deletes (including storage-layer predicates to prevent cross-tenant access), plus tenancy metadata for persisted scores and stored scorer definitions with scoped list APIs. Server routes and client-js methods also accept tenancy parameters so HTTP and SDK usage can enforce the same isolation.

Persisted Trace Scoring APIs (scoreTrace, scoreTraceBatch) + Score Provenance

New scoreTrace() and scoreTraceBatch() let you score already-stored traces without re-running agents, using an existing scorer instance and bounded concurrency for batches. Persisted scores now optionally include batchId, datasetId, and datasetItemId so baseline scoring passes can be grouped and joined back to dataset items across supported stores. …

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