Mastra

Mastra is a TypeScript framework for building AI agents and applications

Originaltext der Quelle · EN

In Aktion ansehen

Produktoberfläche

Inspect a small evaluation dataset

The author’s fictional refund-policy tutorial shows five inputs and their expected criteria in Studio.

Mastra Studio dataset view with five refund-policy inputs and ground-truth criteria
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Lizenz

Lossless PNG-to-WebP conversion; original dimensions and decoded pixels preserved. No crop, upscale or independent site run. Fictional tutorial dataset; no real customer refund case or site-run evaluation is asserted.

Portions of this software are licensed as follows:

- All content that resides under any directory named `ee/` within this
  repository, including but not limited to:
  - `@mastra/core/auth/ee`
  - `@mastra/core/agent-builder/ee`
  - `@mastra/editor/ee`

  is licensed under the license defined in [`ee/LICENSE`](https://github.com/mastra-ai/mastra/blob/main/ee/LICENSE).

- All third-party components incorporated into the Mastra Software are
  licensed under the original license provided by the owner of the
  applicable component.

- Content outside of the above-mentioned directories or restrictions is
  available under the "Apache License 2.0" as defined below.

# Apache License 2.0

Copyright (c) 2025 Kepler Software, Inc.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Produktoberfläche

Review results and the scoring pipeline

The tutorial’s baseline screen connects a five-case dataset, agent and correctness scorer. Displayed scores belong to that example.

Mastra Studio experiment results showing a dataset-agent-scorer pipeline and five case scores
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Lizenz

Lossless PNG-to-WebP conversion; original dimensions and decoded pixels preserved. No crop, upscale or independent site run. Author-published tutorial results, not a general benchmark or an independent site performance claim.

Portions of this software are licensed as follows:

- All content that resides under any directory named `ee/` within this
  repository, including but not limited to:
  - `@mastra/core/auth/ee`
  - `@mastra/core/agent-builder/ee`
  - `@mastra/editor/ee`

  is licensed under the license defined in [`ee/LICENSE`](https://github.com/mastra-ai/mastra/blob/main/ee/LICENSE).

- All third-party components incorporated into the Mastra Software are
  licensed under the original license provided by the owner of the
  applicable component.

- Content outside of the above-mentioned directories or restrictions is
  available under the "Apache License 2.0" as defined below.

# Apache License 2.0

Copyright (c) 2025 Kepler Software, Inc.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Produktoberfläche

Compare answers from two experiments

The author’s comparison view places input, answers and judge explanations side by side for one fictional refund-policy case.

Mastra Studio side-by-side experiment comparison with input, outputs and scorer explanations
Ganzes Bild öffnen
Lizenz

Lossless PNG-to-WebP conversion; original dimensions and decoded pixels preserved. No crop, upscale or independent site run. Retained source labels and timings describe only the illustrated tutorial case. No model ranking or measured site result is inferred.

Portions of this software are licensed as follows:

- All content that resides under any directory named `ee/` within this
  repository, including but not limited to:
  - `@mastra/core/auth/ee`
  - `@mastra/core/agent-builder/ee`
  - `@mastra/editor/ee`

  is licensed under the license defined in [`ee/LICENSE`](https://github.com/mastra-ai/mastra/blob/main/ee/LICENSE).

- All third-party components incorporated into the Mastra Software are
  licensed under the original license provided by the owner of the
  applicable component.

- Content outside of the above-mentioned directories or restrictions is
  available under the "Apache License 2.0" as defined below.

# Apache License 2.0

Copyright (c) 2025 Kepler Software, Inc.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Produktüberblick

Build, observe, and improve agents that run for days with Mastra, the leading TypeScript agent framework.

Originaltext der Quelle · EN
IN DER QUELLE GENANNTE FUNKTIONEN

Was Mastra bietet

  1. 01Define typed agents and tools
  2. 02Compose workflows and memory
  3. 03Inspect traces and evaluations
Originaltext der Quelle · EN
Was es unterscheidet

Was es unterscheidet

It serves code-based agent development with runtime and observability components. Teams still own application logic, integration testing and deployment choices.

Originaltext der Quelle · EN
Für wen es geeignet ist

Für wen es geeignet ist

  • Developers building AI-enabled applications
  • Teams managing repeatable AI workflows
Originaltext der Quelle · EN
VOR DER AUSWAHL

Was zu prüfen ist

  • Eine echte Aufgabe testen und das Ergebnis mit den Anforderungen vergleichen.
  • Prüfen, welche Daten gespeichert, weitergegeben oder zum Training genutzt werden.
  • Aktuelle Preise, Nutzungslimits und Kündigungsbedingungen auf der offiziellen Website prüfen.
Zuletzt geprüft

Offizieller Link am 9. Nov. 2026 geprüft. Funktionsangaben wurden nicht unabhängig getestet.

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