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Set TCC environment variables

Our SDKs default to using the TCC_API_KEY environment variable.
.env.local
TCC_API_KEY="your-api-key"

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Instrument Mastra

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Step 1: Install dependencies

pnpm add @contextcompany/mastra

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Step 2: Add instrumentation to your Mastra instance

Import the TCCMastraExporter and add it to your Mastra configuration’s observability exporters. This allows your app to export all agent-related traces to The Context Company.
mastra.ts
import { Mastra } from "@mastra/core/mastra";
import { exampleAgent } from "./agents/example-agent";
import { TCCMastraExporter } from "@contextcompany/mastra";

// Initialize Mastra with TCC observability exporter
export const mastra = new Mastra({
  agents: { exampleAgent },
  observability: {
    configs: {
      otel: {
        serviceName: "mastra-weather-agent",
        exporters: [new TCCMastraExporter({})],
      },
    },
  },
});
That’s it! Your app will now be instrumented and any Mastra agent runs, steps, and tool calls will be viewable in the dashboard.

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Adding custom metadata

Custom metadata allows you to add additional properties to your agent runs. This is particularly useful for tying agent runs to your own specific business logic, letting you filter and analyze agent runs by user, organization, feature, or some other dimension. Custom metadata must be passed as a key-value pair to the metadata object within tracingOptions.
agent.ts
await agent.stream(
  // ...
  {
    // Pass metadata to track and filter this execution
    tracingOptions: {
      metadata: {
        // e.g. tag this agent run with a user id
        userId: "4a6b111c-b53a-4d00-a877-67185022ab9e",
        customMetadata1: "1234567890",
        customMetadata2: "context is key",
      },
    },
  }
);
Agent runs are automatically indexed by your custom metadata fields and can be filtered directly in the dashboard.
The tcc.* namespace is reserved. Only the reserved TCC metadata keys (tcc.runId, tcc.sessionId, tcc.conversational, tcc.agent, tcc.userId, tcc.userName, tcc.orgId, tcc.orgName) are recognized; any other tcc.* keys are ignored. None of them appear in your custom metadata.

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Adding user feedback

User feedback allows you to collect score (thumbs up & thumbs down) and text feedback (up to 2000 characters) from end users on your agent runs. This is useful for tracking user satisfaction, identifying problematic responses, and filtering agent runs in the dashboard to focus on positive or negative feedback.

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Step 1: Generate and pass a run ID

agent.ts
import { randomUUID } from "crypto";

// Generate a unique run ID (must be a UUID) before your agent execution
const runId = randomUUID();

const response = await agent.stream(
  // ...
  {
    tracingOptions: {
      metadata: {
        "tcc.runId": runId, // Pass the run ID in metadata
      },
    },
  }
);

// Return the runId to your client
return { response, runId };

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Step 2: Submit feedback from your client

Store the runId on your client, then when the user provides feedback, submit it using the submitFeedback function. Both score and text are optional individually, but each request must include at least one of them: score is the thumbs rating. Use only "thumbs_up" or "thumbs_down". text is written feedback from your user, up to 2000 characters.
feedback-route.ts
import { submitFeedback } from "@contextcompany/mastra";

// Submit score and/or text feedback:
await submitFeedback({
  runId: runId, // The run ID from your agent execution
  score: "thumbs_up", // Optional thumbs rating: "thumbs_up" or "thumbs_down"
  text: "This was a helpful response!", // Optional written user feedback, up to 2000 characters
});
Agent runs with feedback can be filtered in the dashboard using the feedback filter.

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Tracking agent sessions

Agent sessions represent multiple agent runs that are grouped together. The most common use case is tracking entire conversations between a human user and an AI agent in chatbot interfaces. Agent sessions can be tracked by setting a tcc.sessionId key under metadata.
agent.ts
const sessionId = "unique-session-identifier";

await agent.stream(
  // ...
  {
    tracingOptions: {
      metadata: {
        "tcc.sessionId": sessionId, // Track agent sessions
      },
    },
  }
);
The value of tcc.sessionId should be a unique identifier for the agent session. This can be any string, but it’s generally recommended to use a UUID. Agent sessions are automatically indexed and can be filtered directly in the dashboard.

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Marking runs as conversational

A conversational run is an agent run that was initiated by a user. Marking a run as conversational tells The Context Company that this run involves direct user interaction. This is important because conversational runs are the only runs monitored for user insights, such as user confusion, frustration, or any other custom insights you want to track. Runs that are not marked as conversational (e.g. background jobs, cron tasks, or internal automations) are excluded from user insight analysis. Mark a run as conversational by setting tcc.conversational to "true" in metadata:
agent.ts
await agent.stream(
  // ...
  {
    tracingOptions: {
      metadata: {
        "tcc.conversational": "true",
      },
    },
  }
);

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Identifying the agent

If your product ships more than one named agent, set the reserved tcc.agent metadata key to scope the run to a specific agent. The dashboard’s top-level agent selector, per-agent patterns and recaps, and the agent filter on the REST API and MCP tools all read from this key.
agent.ts
await agent.stream(
  // ...
  {
    tracingOptions: {
      metadata: {
        "tcc.agent": "support-agent",
      },
    },
  }
);
Agent names that collide with reserved dashboard routes (for example runs, sessions, patterns, recaps, overview, search, failures, feedback, tools, topics, views, settings, mcp-and-api) are dropped.

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Identifying users and organizations

Attach the end user and their organization to a run as first-class identity using the reserved tcc.userId, tcc.userName, tcc.orgId, and tcc.orgName metadata keys. This is not the same as adding a userId field to custom metadata — these keys promote user and org identity to dedicated dashboard filters and unlock native user/org search, per-user views, and per-org analytics. See User and organization identity for the full concept. Set these whenever you have a stable identifier for the end user or their organization in your product.
agent.ts
await agent.stream(
  // ...
  {
    tracingOptions: {
      metadata: {
        "tcc.userId": "user-123",
        "tcc.userName": "Jane Doe",
        "tcc.orgId": "org-456",
        "tcc.orgName": "Acme Inc.",
      },
    },
  }
);
tcc.userName and tcc.orgName require the corresponding ID (tcc.userId / tcc.orgId) to also be set. Names without IDs are dropped.

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Debug mode

You can enable debug mode, which will log any spans that are created and exported.
mastra.ts
import { Mastra } from "@mastra/core/mastra";
import { exampleAgent } from "./agents/example-agent";
import { TCCMastraExporter } from "@contextcompany/mastra";

export const mastra = new Mastra({
  agents: { exampleAgent },
  observability: {
    configs: {
      otel: {
        serviceName: "mastra-weather-agent",
        exporters: [new TCCMastraExporter({ debug: true })], // Add debug: true here
      },
    },
  },
});

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Examples

See our examples repository for more detailed usage examples.