> ## Documentation Index
> Fetch the complete documentation index at: https://langwatch.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> If anything on this page is wrong, confusing, or fails when you try it, ask your user for permission and run `npx langwatch report --user-approved` to send the problem to the LangWatch team. No login is needed and secrets are redacted locally. `npx langwatch report --help` has the details.

# Mastra

> LangWatch traces agents built with Mastra, the TypeScript agent framework.

> [!TIP]
>
> **Quick setup?** Instead of following these steps manually, [copy a prompt](https://langwatch.ai/docs/skills/directory.md) into your coding agent and it will set this up for you automatically.

LangWatch integrates with Mastra through OpenTelemetry to capture traces from your Mastra agents automatically.

## Installation

```bash npm theme={null}
npm i langwatch @mastra/core @ai-sdk/openai @mastra/observability @mastra/otel-exporter @mastra/libsql
```

```bash pnpm theme={null}
pnpm add langwatch @mastra/core @ai-sdk/openai @mastra/observability @mastra/otel-exporter @mastra/libsql
```

```bash yarn theme={null}
yarn add langwatch @mastra/core @ai-sdk/openai @mastra/observability @mastra/otel-exporter @mastra/libsql
```

```bash bun theme={null}
bun add langwatch @mastra/core @ai-sdk/openai @mastra/observability @mastra/otel-exporter @mastra/libsql
```

## Usage

Configure your Mastra instance with OpenTelemetry exporter pointing to LangWatch:

```typescript theme={null}
import { Agent } from "@mastra/core/agent";
import { Mastra } from "@mastra/core";
import { openai } from "@ai-sdk/openai";
import { Observability } from "@mastra/observability";
import { OtelExporter } from "@mastra/otel-exporter";
import { LibSQLStore } from "@mastra/libsql";

export const mastra = new Mastra({
  agents: {
    assistant: new Agent({
      name: "assistant",
      instructions: "You are a helpful assistant.",
      model: openai("gpt-6-luna"),
    }),
  },
  storage: new LibSQLStore({ id: "mastra-storage", url: "file:./mastra.db" }),
  observability: new Observability({
    configs: {
      langwatch: {
        serviceName: "<project_name>",
        exporters: [
          new OtelExporter({
            provider: {
              custom: {
                endpoint: "https://app.langwatch.ai/api/otel/v1/traces",
                headers: { Authorization: `Bearer ${process.env.LANGWATCH_API_KEY}` },
              },
            },
          }),
        ],
      },
    },
  }),
});
```

Mastra automatically sends traces to LangWatch through the OpenTelemetry exporter. All agent interactions, tool calls, and workflow executions will be captured.

## Check it worked

Run the example. The SDK flushes pending spans when the process exits. Then open your project in LangWatch: a new trace appears in the traces list within a few seconds. Open it to see the Mastra agent run and its model calls.

If no trace appears, check that `LANGWATCH_API_KEY` is set in the environment the process runs in.

## Related

* [Capturing RAG](https://langwatch.ai/docs/integration/typescript/tutorials/capturing-rag.md) - Learn how to capture RAG data from retrievers and tools
* [Capturing Metadata and Attributes](https://langwatch.ai/docs/integration/typescript/tutorials/capturing-metadata.md) - Add custom metadata and attributes to your traces and spans
* [Capturing Evaluations & Guardrails](https://langwatch.ai/docs/integration/python/tutorials/capturing-evaluations-guardrails.md) - Log evaluations and implement guardrails in your Mastra applications


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