Claude Platform Docs

Get Token Usage Over Time

GET/v1/organizations/analytics/usage_report

[Legacy] Get token usage over time across a date range.

Returns token usage bucketed by minute, hour, or day, optionally broken down by one or more group_by[] dimensions, such as product or model. Available to organizations on a Claude Enterprise plan. Requires an API key with the read:analytics scope.

This endpoint is one of the legacy Claude Enterprise usage and cost reports. For new integrations, use GET /v1/organizations/analytics/usage in the Usage and Cost Analytics API instead. To move an existing integration, see Migrate from the Claude Enterprise usage and cost reports.

Query parameters
starting_at: string

Start of range, inclusive. RFC 3339 tz-aware. Must be within the last 365 days and no earlier than 2026-01-01T00:00:00Z.

formatdate-time
bucket_width: optional "1d" or "1h" or "1m"

Time bucket granularity.

default1d
One of the following:
"1d"
"1h"
"1m"
claude_tag_categories: optional array of BetaAnalyticsClaudeTagCategory

Filter to Claude Tag (Claude in Slack) usage in specific spend categories. Usage with no category never matches. dm usage is reported under the user's product rather than claude-tag, so combining this filter with products[]=claude-tag excludes it. Use group_by[]=claude_tag_category to break out per-category values.

maxItems100
One of the following:
"dm"
"engaged"
"monitoring"
"proactive"
"scheduled"
claude_tag_user_ids: optional array of string

Filter to Claude Tag (Claude in Slack) usage attributed to specific Slack users, by Slack user ID (for example U0123ABCDEF), not claude.ai user ID. Usage that is not Claude Tag, and Claude Tag usage not attributed to a single user, never matches. Use group_by[]=claude_tag_user_id to break out per-user values.

maxItems100
context_windows: optional array of BetaAnalyticsContextWindow

Filter to specific context-window pricing tiers. Use group_by[]=context_window to break out per-tier values.

maxItems100
One of the following:
"0-200k"
"200k-1M"
ending_at: optional string

End of range, exclusive. When omitted, defaults to the earlier of now and starting_at + 31 days. The range may span at most 31 days.

formatdate-time
group_by: optional array of "claude_tag_category" or "claude_tag_user_id" or "context_window" or 6 more

Dimensions to break each time bucket out by. Defaults to no grouping (one total per bucket). Each bucket reports at most its top 100 groups; a group beyond that cap has no row in that bucket (there is no remainder row), so grouped buckets are not exhaustive when a dimension has more than 100 distinct values.

maxItems100
One of the following:
"claude_tag_category"
"claude_tag_user_id"
"context_window"
"inference_geo"
"model"
"product"
"rbac_group_id"
"slack_channel_id"
"speed"
inference_geos: optional array of BetaAnalyticsInferenceGeoFilter

Filter to specific inference regions. not_available matches rows where the region is unset. Use group_by[]=inference_geo to break out per-region values.

maxItems100
One of the following:
"global"
"not_available"
"us"
limit: optional number

Maximum number of time buckets per page. Defaults and caps vary by bucket_width (1d: default 7, max 31; 1h: default 24, max 168; 1m: default 60, max 256).

minimum1
models: optional array of string

Models to include. Defaults to all models. Use group_by[]=model to break out per-model values.

maxItems100
page: optional string

Opaque cursor from a previous response's next_page field.

products: optional array of BetaAnalyticsProductFilter

Product surfaces to include. Defaults to all products. Use group_by[]=product to break out per-product values.

maxItems100
One of the following:
"chat"
"chat_cowork_unified"
"claude-tag"
"claude_code"
"claude_design"
"claude_in_chrome"
"cowork"
"office_agent"
rbac_group_ids: optional array of string

Filter to usage attributed to specific RBAC groups. Accepts tagged RBAC group IDs (rbac_group_...) or bare group UUIDs. A row matches when the user belonged to any of the listed groups on the (UTC) day the usage occurred; usage with no group attribution never matches.

maxItems100
slack_channel_ids: optional array of string

Filter to usage originating from specific Slack channels. Use group_by[]=slack_channel_id to break out per-channel values.

maxItems100
speeds: optional array of "fast" or "standard"

Filter to fast or standard inference mode. Use group_by[]=speed to break out per-mode values.

maxItems100
One of the following:
"fast"
"standard"
user_ids: optional array of string

Filter to specific users by tagged user ID.

maxItems100
Headers
"anthropic-version": optional string

The version of the Claude API you want to use.

Read more about versioning and our version history here.

Returns
data: array of BetaAnalyticsUsageReportTimeBucket { ending_at, results, starting_at }

Time buckets for this page, oldest first: one per bucket_width interval, including intervals with no data (their results list is empty). A page holds at most limit buckets.

ending_at: string

End of the time bucket (exclusive) in RFC 3339 format.

formatdate-time
results: array of BetaAnalyticsUsageBucketedResult { cache_creation, cache_read_input_tokens, claude_tag_category, 12 more }

Rows for this time bucket. Empty when the bucket has no data; otherwise a single combined row when group_by[] is omitted, or one row per group (subject to the per-bucket group cap described on the group_by[] parameter).

cache_creation: BetaCacheCreation { ephemeral_1h_input_tokens, ephemeral_5m_input_tokens }

The number of input tokens for cache creation.

ephemeral_1h_input_tokens: number

The number of input tokens used to create the 1 hour cache entry.

default0
minimum0
ephemeral_5m_input_tokens: number

The number of input tokens used to create the 5 minute cache entry.

default0
minimum0
cache_read_input_tokens: number

The number of input tokens read from the cache.

claude_tag_category: BetaAnalyticsClaudeTagCategory or null

Claude Tag (Claude in Slack) spend category: engaged (a person addressed Claude in a channel or thread), proactive (Claude responded without being addressed), scheduled (a scheduled routine ran), monitoring (Claude watching a channel it was asked to monitor), or dm (direct messages with Claude). Populated only when claude_tag_category is in group_by[]; null for usage that is not Claude Tag. Direct-message usage is billed to the individual user and is reported under that user's product, not under claude-tag. New categories may be added over time.

One of the following:
"dm"
"engaged"
"monitoring"
"proactive"
"scheduled"
claude_tag_user_id: string or null

Slack user ID (for example U0123ABCDEF) of the member the Claude Tag (Claude in Slack) usage is attributed to, not a claude.ai user ID. Populated only when claude_tag_user_id is in group_by[]; null for usage that is not Claude Tag and for Claude Tag usage that is not attributed to a single user (for example monitoring, and proactive usage Claude initiated), so per-user rows can sum to less than the Claude Tag total. Cannot be combined with group_by[]=rbac_group_id or the rbac_group_ids[] filter.

context_window: BetaAnalyticsContextWindow or null

Context-window pricing tier of the usage or cost. Null unless context_window is in group_by[]; it can also be null on grouped rows with no context-window tier, such as code execution.

One of the following:
"0-200k"
"200k-1M"
inference_geo: "global" or "us" or null

Inference region of the usage or cost. Null unless inference_geo is in group_by[]; it can also be null on grouped rows where the region is not set (the rows that inference_geos[]=not_available matches).

One of the following:
"global"
"us"
model: string or null

Model that produced the usage or cost, as a model name in the form the models[] filter accepts (for example, claude-opus-5-5). Null unless model is in group_by[]; it can also be null on grouped rows whose usage or cost is not attributed to a specific model, such as code execution.

output_tokens: number

The number of output tokens generated.

product: string or null

Product surface that produced the usage or cost. Null unless product is in group_by[]; it can also be null on grouped rows whose usage cannot be attributed to a known surface. Values include chat, claude_code, cowork, office_agent, claude_in_chrome, claude_design, claude-tag, and chat_cowork_unified. claude-tag is Claude Tag, the Claude product in Slack. chat_cowork_unified is Chat and Cowork unified, Cowork's features inside claude.ai chat: chat and Cowork usage by a member who has it turned on is reported under this value instead of chat or cowork. It is accepted as a filter only where Chat and Cowork unified is available. Some unattributed usage is reported as "other".

rbac_group_id: string or null

RBAC group (team) the usage is attributed to, in the public tagged rbac_group_... spelling — the same spelling the activity resources use for this key, so the same team has one id across resources and it round-trips as an rbac_group_ids[] filter value. Populated only when rbac_group_id is in group_by[]. Any-membership semantics: a user in several groups contributes their full usage to each of those groups' rows, so the named-group rows overlap and their sum can exceed the org total. A null value is the single unassigned row: users in no group on that (UTC) day. For the true org total, run the same query without group_by[].

requests: number or null

Number of API requests in this row's scope. For sandbox / code-execution events, this counts execution spans rather than HTTP requests (these rows surface with product: null).

server_tool_use: BetaAnalyticsServerToolUse { web_search_requests }

Server-side tool usage metrics.

web_search_requests: number

The number of web search requests made.

slack_channel_id: string or null

Slack channel the usage originated from. Populated only when slack_channel_id is in group_by[]; null for usage outside Slack (and for rows recorded before channel attribution was enabled).

speed: "fast" or "standard" or null

Inference speed mode of the usage or cost: fast or standard. Null unless speed is in group_by[].

One of the following:
"fast"
"standard"
uncached_input_tokens: number

The number of uncached input tokens processed.

starting_at: string

Start of the time bucket (inclusive) in RFC 3339 format.

formatdate-time
data_refreshed_at: string or null

RFC 3339 timestamp of the export this response was served from. Null when no export yet covers any part of the requested range, in which case every bucket's results list is empty. Buckets beyond this watermark are incomplete; for stable results, set ending_at to this value or earlier. Data is typically refreshed every 4 hours. Values can be revised as late events arrive and reconciliation runs, until about 7 days after the end of the calendar month the usage falls in; for example, values for October 1 can change until about November 7.

formatdate-time
has_more: boolean

Whether another page is available. When true, pass next_page as the page parameter to fetch it.

next_page: string or null

Opaque cursor for the next page, or null when has_more is false. Pass it as the page parameter, keeping the other parameters unchanged. A cursor can expire after the underlying data refreshes; the request then returns HTTP 410 and pagination must restart from the first page.

organization_id: string

ID of the Organization.

Get Token Usage Over Time
curl https://api.anthropic.com/v1/organizations/analytics/usage_report \
    -H 'anthropic-version: 2026-10-21' \
    -H "Authorization: Bearer $ANTHROPIC_API_KEY"
Returns Examples
Response 200
{
  "data": [
    {
      "ending_at": "2019-12-27T18:11:19.117Z",
      "results": [
        {
          "cache_creation": {
            "ephemeral_1h_input_tokens": 0,
            "ephemeral_5m_input_tokens": 0
          },
          "cache_read_input_tokens": 0,
          "claude_tag_category": "dm",
          "claude_tag_user_id": "U0123ABCDEF",
          "context_window": "0-200k",
          "inference_geo": "global",
          "model": "claude-opus-5-5",
          "output_tokens": 0,
          "product": "chat",
          "rbac_group_id": "rbac_group_012rppKaSVsmTo6NqRDXQXNF",
          "requests": 0,
          "server_tool_use": {
            "web_search_requests": 10
          },
          "slack_channel_id": "C0123ABCDEF",
          "speed": "fast",
          "uncached_input_tokens": 0
        }
      ],
      "starting_at": "2019-12-27T18:11:19.117Z"
    }
  ],
  "data_refreshed_at": "2019-12-27T18:11:19.117Z",
  "has_more": true,
  "next_page": "next_page",
  "organization_id": "org_013FP9SaFPBg7Kw7fetjn6cF"
}