# Plutus (remote · console.plutus-cloud.com)

Query cloud, AI and SaaS spend across 25+ providers: costs, budgets, anomalies, unit economics.

- Trust score: 90/100 (high trust)
- Change this week: +4
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-20

## Components

- remote · `console.plutus-cloud.com`: 90/100 (this document), [markdown](https://verifymcp.io/servers/com-plutus-cloud-plutus-cost-data/api-mcp.md), [page](https://verifymcp.io/servers/com-plutus-cloud-plutus-cost-data/api-mcp)

## Channel facts

- Endpoint: `https://console.plutus-cloud.com/api/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `2.0.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-20.

- **Endpoint Security**: 97/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation is enforced on tool calls, advertised via RFC 9728 protected-resource metadata. Discovery is public, which costs nothing: no tool can be invoked without a token.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
  - The authorisation server supports Client ID Metadata Documents, the current MCP client-registration mechanism.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 79/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 6356 tokens (~205/item across 31 items; 31 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 67/100
  - Stability observed for 20 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 92/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 77% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 31 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 31 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

## Install

### How do I install the Plutus MCP server?

Plutus is a hosted endpoint at https://console.plutus-cloud.com/api/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http com-plutus-cloud-plutus-cost-data 'https://console.plutus-cloud.com/api/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "com-plutus-cloud-plutus-cost-data": {
      "url": "https://console.plutus-cloud.com/api/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "com-plutus-cloud-plutus-cost-data": {
      "type": "http",
      "url": "https://console.plutus-cloud.com/api/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.com-plutus-cloud-plutus-cost-data]
url = "https://console.plutus-cloud.com/api/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-plutus-cloud-plutus-cost-data": {
      "type": "remote",
      "url": "https://console.plutus-cloud.com/api/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-plutus-cloud-plutus-cost-data --url 'https://console.plutus-cloud.com/api/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-plutus-cloud-plutus-cost-data:
    url: "https://console.plutus-cloud.com/api/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "com-plutus-cloud-plutus-cost-data": {
      "Transport": "http",
      "Url": "https://console.plutus-cloud.com/api/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add com-plutus-cloud-plutus-cost-data -t streamable-http -u 'https://console.plutus-cloud.com/api/mcp'
```

### Other

```json
{
  "mcpServers": {
    "com-plutus-cloud-plutus-cost-data": {
      "type": "http",
      "url": "https://console.plutus-cloud.com/api/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-20 (score 90, +1)

No change was recorded against any check on this day. Stability & Change Management went from 63 to 67. That category is still filling its 30-day observation window: 19 days of observed history at the previous scan, 20 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-18 (score 89, +1)

No change was recorded against any check on this day. Stability & Change Management went from 57 to 60. That category is still filling its 30-day observation window: 17 days of observed history at the previous scan, 18 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-17 (score 88, +8)

- [security improvement] Judged manipulation: unverified → pass
- [functional improvement] Schema quality: unverified → excellent

### 2026-09-16 (score 80, −7)

- [security regression] Judged manipulation: pass → unverified
- [functional regression] Schema quality: excellent → unverified
- [functional] New tool “explain_cost_change”

### 2026-09-14 (score 87, +1)

- [security] Tool “list_anomalies” rewrote its description, which is the text the model reads
- [functional] New prompt “anomaly-triage”
- [functional] New prompt “billed-vs-amortized-explainer”
- [functional] New prompt “budget-setup-assistant”
- [functional] New prompt “commitment-expiry-watch”
- [functional] New prompt “month-end-chargeback-pack”
- [functional] New prompt “tag-coverage-remediation”
- [functional] New prompt “tag-coverage-review”
- [functional] New prompt “unit-economics-review”
- [functional] New tool “list_commitment_expirations”

### 2026-09-11 (score 86, +1)

No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-09 (score 85, +1)

No change was recorded against any check on this day. Stability & Change Management went from 27 to 30. That category is still filling its 30-day observation window: 8 days of observed history at the previous scan, 9 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-07 (score 84, +1)

No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

## MCP tools (31)

### `list_cost_sources` (~128 tokens)

List the cost-source providers (AWS, GCP, Anthropic, etc.) enabled for this account. Each row's cost_basis says where that provider's money figures come from: "invoiced" = amounts the provider actually charged; "estimated_from_provider_rates" = an estimate built from the provider's own published rates, because it exposes no historical billing API; "estimated_from_static_rates" = an estimate built from a list-rate card Plutus maintains, which will not reflect rates the customer negotiated. Qualify any total that includes an estimated source rather than reporting it as billed spend.

### `query_costs` (~1052 tokens)

Query time-bucketed spend for this account, optionally broken down by a dimension (service, region, linked_account, usage_type, operation, or identity) or by a custom cost-allocation tag (see list_cost_tags), and filtered by dimension values. `identity` is per-actor spend (e.g. an OpenAI or Anthropic api_key_id) where a provider's cost/usage API can group by it; not every provider populates it. Mirrors the GET /api/analytics endpoint used by the Plutus dashboard charts. All amounts are in USD, converted from each provider's own billing currency at the rate in effect on the day of the charge; the response states this in its `currency` field.

A row carries `cost_basis` only when its `cost` figure is an estimate rather than a real invoiced charge — e.g. Anthropic's identity-grain rows, priced from Anthropic's own published per-token rates because Anthropic's cost API has no per-key breakdown at all. Absent (null) `cost_basis` means the figure is invoiced. Always qualify an estimated figure as such when relaying it — do not present it with the same confidence as an invoiced one.

Where a provider reports usage alongside cost, a row also carries `quantity` and its `unit` (e.g. tokens, GB-month), plus a derived `cost_per_unit` in that same USD base. Always read `cost_per_unit` together with `cost_per_unit_label`, which names the denominator it is quoted against: token costs are quoted per 1,000 tokens ("per 1k tokens", `cost_per_unit_scale: 1000`), NOT per single token. All four fields are null when the provider reports no usage, and also when the rows behind a group carry more than one unit — a total mixing tokens and GB-month is not a quantity, so none is given.

The response also carries `coverage.complete_through`: cost data for the newest periods often has not landed yet (it arrives hours-to-a-day after the period it covers), so `rows` may end before `end_date` without that being a gap in spend — the newest period(s) simply aren't complete yet. `coverage.lagging_so…

Input parameters:

- `breakdown_by` (string): Dimension to break spend down by, or "tag" to break down by a virtual cost-allocation tag_key (see list_cost_tags) — requires tag_key.
- `cost_metric` (string): Which cost figure to sum (default: "billed"). "amortized" spreads prepaid commitments (AWS Reserved Instances/Savings Plans, Azure reservations) across the term they cover instead of showing the full…
- `cost_source_ids` (array): Restrict to these provider ids (defaults to all enabled providers)
- `end_date` (string): ISO-8601 end of the date range (exclusive)
- `filter_cluster` (array): Restrict to these cluster values
- `filter_identity` (array): Restrict to these identity values
- `filter_linked_account` (array): Restrict to these linked_account values
- `filter_namespace` (array): Restrict to these namespace values
- `filter_operation` (array): Restrict to these operation values
- `filter_region` (array): Restrict to these region values
- `filter_resource_id` (array): Restrict to these resource_id values
- `filter_service` (array): Restrict to these service values
- `filter_usage_type` (array): Restrict to these usage_type values
- `filter_workload` (array): Restrict to these workload values
- `group_by` (string): Time bucket size (default: day)
- `secondary_breakdown_by` (string): A second dimension to break spend down by simultaneously with breakdown_by. Only pairs that some provider actually stores together on the same row are supported — e.g. (service, region), (service, li…
- `start_date` (string): ISO-8601 start of the date range (inclusive)
- `tag_key` (string): Required when breakdown_by is "tag" — one of the tag_keys returned by list_cost_tags

### `list_savings_recommendations` (~271 tokens)

List active cost-reduction recommendations for this account — sourced from each provider's own already-computed engine (AWS Cost Explorer, Azure Advisor, GCP Recommender), not something Plutus computes itself. `type` is one of: `terminate` (an idle resource to shut down), `modify` (an overprovisioned one to downsize), `commitment_savings_plan` or `commitment_reservation` (a commitment worth *buying* — an AWS Savings Plan / Reserved Instance, Azure reservation or savings plan, or GCP committed use discount). Commitment rows have no `current_instance_type`/`recommended_instance_type` — they are a purchase, not an instance swap; their term, payment option, lookback window and hourly commitment are in `detail`. Only one term/payment/lookback variant per commitment is surfaced (AWS: 30-day lookback, 1-year, no upfront — Cost Explorer's own console default), so do not report these as the only commitment options available. Mirrors GET /api/accounts/:accountId/savings-recommendations. Each recommendation carries the provider's own figure in its own `currency`; the total is in USD (stated in the response's `currency` field), since providers may bill in different ones.

### `list_commitment_utilization` (~86 tokens)

List Reservation (RI) and Savings Plan utilization/coverage snapshots for this account — sourced from AWS Cost Explorer's own GetReservationUtilization/GetSavingsPlansUtilization APIs, one snapshot per commitment type per month. Shows how much of a purchased commitment is actually being used and its net savings vs on-demand. Mirrors GET /api/accounts/:accountId/commitment-utilization.

### `list_commitment_expirations` (~182 tokens)

List this account's Reserved Instance / Savings Plan / Azure Reservation commitments with their expiration dates, ordered soonest-first. `days_until_expiration` is computed server-side against the current UTC date (negative means already expired — rows are not pruned immediately on expiry, so check the sign). `latest_utilization_percentage` is the commitment TYPE's most recent monthly aggregate utilization (from list_commitment_utilization) applied to every active commitment of that type — there is no true per-commitment utilization API, so this is the closest real signal for "is this expiring commitment even being used," not an exact per-commitment figure. The same 30/14/7/1-day thresholds and 80% cutoff the automatic expiration alert uses are the right ones to flag here too, for consistency with what a subscribed channel already receives.

### `list_cost_tags` (~159 tokens)

List the virtual cost-allocation tag_keys defined for this account (e.g. "team", "product"), each with the cost_entries grain it's locked to and how many rules map dimension values to a tag_value. Use a tag_key with query_costs (breakdown_by: "tag") to see spend broken down by it. redistribute_bucket, when non-null, names a bucket (often "Untagged") whose spend is dissolved into the other tag_values in proportion to their own attributed spend in the same period — so that bucket will not appear in a query_costs breakdown for this tag_key, and the other values include a proportional share of it. It reappears only in periods where there was no other spend to redistribute against.

### `list_anomalies` (~545 tokens)

List detected cost anomalies for this account over a trailing lookback window — the real output of Plutus's nightly anomaly detector (severity, baseline vs. current spend, and what drove a tag-level spike), not something recomputed here from raw spend. Prefer this over eyeballing query_costs for "did anything spike" — the detector already accounts for day-of-week baselines and an absolute-dollar noise floor that a naive comparison would miss or over-trigger on.

Capped at 200 rows, most recent first; `days` (default 30, max 90) bounds the lookback. `kind` is "service" or "tag". `current_cents`/`baseline_cents`/`delta_cents` are the USD base. `suppressed: true` means a human has marked this exact signature (provider+service, or tag_key+tag_value) as expected — mention it but do not lead with it as a live problem. `driven_by` is null when driver attribution was not measured for this anomaly and `[]` when it WAS measured and found no dominant driver — those mean different things. Its entries differ by anomaly kind: a tag anomaly's entries are service-shaped (`service`/`cost_source_id`/`share_pct` — the services that fed the tag_value's spike); a service anomaly's entries, when the account has resource-grain detection enabled, are resource-shaped (`resource_id`/`resource_type`/`share_pct` — the specific resources, e.g. an EC2 instance or Lambda function, that drove that service's spike). Report a resource entry as a decomposition of the same service anomaly, never as a separate anomaly of its own. `correlated_events` is the service-anomaly counterpart: deploy/incident/release activity that was unusual (above the account's own baseline rate) in the 2-day window ending on the spike day, ranked by share of that excess. Same null-vs-`[]` distinction — null is "not measured" (a tag anomaly, or a row recorded before this shipped), `[]` is "measured and nothing was unusual". It is account-scoped and temporal: it does NOT claim the event caused this particular service's spend…

Input parameters:

- `days` (integer): Trailing lookback window in days (default: 30)

### `explain_cost_change` (~519 tokens)

Explain a specific cost change: which timeline events line up with it, how strongly, and how much of the move Plutus could account for. Ask this about any point on a cost chart — it is not limited to anomalies the detector flagged (use list_anomalies for those; each already carries the same explanation).

RENDER `explanation.sentences` AS WRITTEN. They are generated under a strict discipline and are the only phrasing this data supports: Plutus reports temporal and dimensional evidence, never causation. Each candidate carries a `claim` of "coincides" (temporal proximity only — the common case), "consistent_with" (proximity plus a confirmed link between that event source and this cost entity) or "accounts_for" (a known dollar amount that matches the move). Do not upgrade one to another, do not say an event "caused" or "led to" the change, and do not merge several candidates into a single narrative.

Three separate numbers, never interchangeable: `change_evidence` is how sure we are a real change-point exists at all; `attribution_completeness` is what fraction of the move was localized to a specific part of the bill (a low value means "we do not know what this spend is yet", which is NOT the same as "nothing explains it"); `p_cause` is per candidate, and sums with `p_unknown` to 1. `tier: "unknown"` means we looked and found nothing that lines up — say that, rather than reaching for the top-ranked candidate anyway. Confidence is capped at 0.60 by design; there is no "high" tier today.

Body: `dimension` + `value` name the slice (e.g. service=AmazonEC2), optional `cost_source_id` narrows it, and exactly one of `day` or `range` says when. A range is narrowed to the single biggest-moving day inside it, reported as `explained_day`. Mirrors POST /api/accounts/:accountId/cost-changes/explain.

Input parameters:

- `cost_source_id` (string): Narrow to one cost source, e.g. "aws"
- `day` (string): YYYY-MM-DD — the day to explain
- `dimension` (string, required): Which dimension names the slice
- `range` (object): Half-open YYYY-MM-DD range; narrowed to its biggest-moving day
- `value` (string, required): The dimension value that moved, e.g. "AmazonEC2"

### `list_anomaly_suppressions` (~89 tokens)

List this account's active anomaly suppressions — signatures (a provider+service pair, or a tag_key+tag_value) a human has marked as expected, so the detector stops surfacing them. Each has an `expires_at` (null = indefinite). Mirrors GET /api/accounts/:accountId/anomaly-suppressions. Creating/deleting a suppression is not available over MCP.

### `list_tag_recommendations` (~118 tokens)

List suggested cost-allocation tag rules this account doesn't have yet — high-spend values currently falling through to "Untagged" for an existing tag_key, or a provider-native tag worth promoting into a virtual tag_key of its own (see list_cost_tags). Each recommendation carries `estimated_monthly_spend_cents` (USD base) it would newly cover. Mirrors GET /api/accounts/:accountId/tag-recommendations. Accepting or dismissing a recommendation is a UI/REST-only action, not available over MCP.

### `list_data_health` (~142 tokens)

List sync health for every cost/event/usage connection this account has — last synced time, next scheduled sync, the outcome of its most recent run, and `is_overdue` (no successful sync within twice the connection's own effective sync interval). `status` is only ever set on a successful sync and is never flipped back on failure, so `is_overdue` — not `status` — is the real signal that a connection has gone stale. Check this before asserting that recent cost or usage data is complete, especially right before calling query_costs or query_usage for a very recent date range. Mirrors GET /api/accounts/:accountId/data-health.

### `list_scheduled_reports` (~91 tokens)

List this account's scheduled cost digests — cadence, scope (whole account, one cost source, or one cost-allocation tag value), destination alert channel, and when the next one is due. `next_period_label` names the concrete date range the next digest will cover. Mirrors GET /api/accounts/:accountId/scheduled-reports. Creating/editing a scheduled report is not available over MCP.

### `list_dashboard_widget_catalog` (~200 tokens)

List the built-in ("preset") dashboard widgets available to place with create_dashboard/set_dashboard_widgets — small `kpi` stat tiles and larger `widget` data cards, each with the id (`catalog_id`) a {"kind": "preset", "catalog_id": "..."} widget spec references. There is no preset chart: to put a trend chart on a dashboard, build one inline with a {"kind": "custom_chart", ...} spec instead of a catalog_id — see create_dashboard's description for that shape.

The response also carries `grid_cols` (the canvas width every widget's x/w is measured against) and `size_bounds`, the min/max `w`/`h` each widget TYPE (`kpi`/`chart`/`widget` — not each individual catalog_id) accepts when a spec overrides its default size — use these before calling create_dashboard/set_dashboard_widgets with an explicit `w`/`h`.

### `list_dashboards` (~73 tokens)

List this account's org-shared dashboards — visible to every account member. Does not include any member's PERSONAL dashboard: those live in one specific signed-in user's own browser session and have no id an account-level MCP key can address. Use a returned `id` with get_dashboard, set_dashboard_widgets or delete_dashboard.

### `get_dashboard` (~111 tokens)

Fetch one org-shared dashboard's full layout — its placed widgets, custom metrics and custom charts, and their grid positions. A `widgets` entry references a preset catalog_id (see list_dashboard_widget_catalog); `customMetrics`/`customCharts` carry their own full config inline. Call this before set_dashboard_widgets if you want to keep some of what's already there rather than replacing the whole set — that tool always replaces everything.

Input parameters:

- `dashboard_id` (string, required): A shared dashboard id from list_dashboards

### `list_unit_metrics` (~139 tokens)

List this account's saved unit-economics metrics — each one a cost ÷ business-unit ratio such as "cost per 1k API requests" or "infra cost per order". `numerator_scope` says which slice of spend is on top (the whole account, one cost source, or one cost-allocation tag_value — see list_cost_tags), `denominator_metric` names the usage metric counting the business units, and `denominator_scale` is the readability factor the ratio is quoted at (1, 1000 or 1000000). Pass an id to query_unit_costs to compute one over a date range.

### `query_unit_costs` (~617 tokens)

Compute one of this account's saved unit-economics metrics (see list_unit_metrics) over a date range — the cost of a slice of spend divided by the business units it produced. Each row carries `cost` (the numerator, in the USD base like every other figure this server returns), `quantity` (the denominator, a raw count with no currency), and `unit_cost`.

CRITICAL: `unit_cost` is null whenever it could not be computed, and null does NOT mean zero. It means one half of the fraction is missing for that period — either no usage was ingested (a telemetry gap) or no cost data has landed yet. Do not describe a null unit cost as a cost of zero, and do not average nulls in as zeroes; the `coverage` block reports how many rows are affected and why. Always read `unit_cost` together with `denominator_label` (e.g. "per 1k requests"), which names what it is quoted against — a per-1k figure reported as a per-request figure is wrong by three orders of magnitude.

The series stops at `coverage.complete_through` rather than at the requested end_date whenever cost data for the newest periods has not arrived yet (it lands hours-to-a-day after the period it covers, while usage telemetry is pushed live). A short series is therefore normal and is NOT evidence that spend or usage stopped — say what it is complete through instead. `coverage.lagging_sources`, when non-empty, is the opposite case: a cost source that is behind or has stopped reporting, so recent periods are missing its spend and their unit costs read lower than the truth.

If `numerator_status.available` is false, the cost source this metric measured has been removed from the account and `rows` is empty. That is a broken definition, not a period of zero spend — never report it as costs having fallen.

Amounts are billed cost, never amortized, regardless of any cost_metric used elsewhere. A tag-scoped metric inherits that tag_key's allocation policy, so its numerator may include a redistributed share of shared spend (see list_co…

Input parameters:

- `end_date` (string): ISO-8601 end of the date range (exclusive)
- `group_by` (string): Time bucket size (default: day)
- `start_date` (string): ISO-8601 start of the date range (inclusive)
- `unit_metric_id` (integer, required): id of a metric returned by list_unit_metrics

### `query_usage` (~231 tokens)

Query time-bucketed usage telemetry this account's own backend has pushed or synced in (e.g. API request counts, tokens processed) — the raw data unit-economics metrics divide cost by (see list_unit_metrics/query_unit_costs), inspected directly rather than through a pre-defined ratio. `quantity` is a raw count with no currency — never treat it as money. Optionally broken down by `external_customer_id` when the pushed rows carry one. Mirrors GET /api/usage.

Input parameters:

- `breakdown_by` (string)
- `end_date` (string): ISO-8601 end of the date range (exclusive)
- `filter_external_customer_id` (array)
- `filter_metric` (array): Restrict to these metric names
- `filter_source_id` (array): Restrict to usage pushed/synced under these usage-source ids
- `group_by` (string): Time bucket size (default: day). "hour" is only supported for ranges of 7 days or less.
- `start_date` (string): ISO-8601 start of the date range (inclusive)

### `list_usage_dimensions` (~111 tokens)

List the distinct values seen for a usage dimension ("metric" or "external_customer_id") over a date range — useful for discovering filter values before calling query_usage. Each entry pairs the raw `value` with a `label` (for external_customer_id, the customer's name from account_customers when known, falling back to the id itself). Mirrors GET /api/usage/dimensions.

Input parameters:

- `dimension` (string, required)
- `end_date` (string)
- `start_date` (string)

### `query_events` (~283 tokens)

Query this account's business-event timeline (GitHub releases/PRs, PagerDuty incidents, Jira issues, GitLab, Salesforce onboarding/churn, Stripe subscription created/canceled, Vercel production deploys, Linear issue creation, Sentry newly reported errors) — the same events overlaid on the Cost/Event Explorer charts. Always scope with start_date/end_date: there is no pagination and results are capped at 5000 rows (oldest-first), so an unscoped query over a long history may be silently truncated. Carries no cost figure. Mirrors GET /api/events.

Input parameters:

- `end_date` (string): ISO-8601 end of the date range (inclusive)
- `event_type` (array): Restrict to these event types, e.g. "issue_created", "deploy"
- `meta_repo` (array): Restrict to these GitHub repos (metadata.repo) — only narrows events that carry a repo; events with no repo (e.g. Salesforce onboarding/churn) are unaffected regardless of value
- `q` (string): Free-text, case-insensitive substring match against the event title
- `source_id` (string): Restrict to one event source, e.g. "github", "pagerduty", "jira"
- `start_date` (string): ISO-8601 start of the date range (inclusive)

### `list_event_facets` (~108 tokens)

List the distinct values seen for a faceted event metadata field over a date range — currently just "repo" (every GitHub repo with at least one event), the same facet the Event Explorer's repo picker uses. Useful for discovering query_events' meta_repo filter values before calling it. Mirrors GET /api/events/facets.

Input parameters:

- `attr` (string, required)
- `end_date` (string)
- `source_id` (string)
- `start_date` (string)

### `list_cost_tag_rules` (~246 tokens)

List the actual match rules for one of this account's cost-allocation tag_keys (see list_cost_tags) — which dimension values (or provider-native tag) map to which tag_value, and in what priority order. Rules are evaluated in ascending priority and the first match wins; spend matching no rule falls to "Untagged". Mirrors GET /api/accounts/:accountId/cost-tags/:tagKey/rules. IMPORTANT — a rule is NOT always a single assignment: when its `splits` field is non-null it is an array of {tag_value, weight} with weights summing to 1, and matched spend is divided across those tag_values by weight rather than going wholly to the rule's own tag_value. On a split rule, `tag_value` is only the rule's display label (e.g. "Shared EKS cluster") and no spend is attributed to it. Do not describe a rule with splits as assigning its spend to one team. Note also that some spend may be reallocated after these rules run — see list_cost_tags' redistribute_bucket.

Input parameters:

- `tag_key` (string, required): One of the tag_keys returned by list_cost_tags

### `list_cost_source_tag_keys` (~108 tokens)

List distinct provider-native tag/label keys actually present in this account's cost data (AWS Cost Allocation Tags, GCP/Hetzner labels, Azure tags) — useful for discovering what a "tags.<key>" cost-tag-rule match could reference before creating one. Only ever populated on grain='service' rows. Omit cost_source_id to search across every enabled provider.

Input parameters:

- `cost_source_id` (string): Restrict to one provider, e.g. "gcp"

### `list_cost_source_tag_values` (~83 tokens)

List distinct values seen for one provider-native tag/label key (see list_cost_source_tag_keys) in this account's cost data.

Input parameters:

- `cost_source_id` (string): Restrict to one provider, e.g. "gcp"
- `tag_name` (string, required): A tag key returned by list_cost_source_tag_keys, e.g. "team"

### `list_teams` (~65 tokens)

List this account's teams (user groups) with their members and the cost-tag tag_value each is reserved under — team-scoped budgets (create_budget with scope_type: "team") reference a team's id as scope_ref. Mirrors GET /api/accounts/:accountId/teams.

### `list_budgets` (~134 tokens)

List this account's spend budgets with their current-cycle status (spend so far, projected total, ok/warning/exceeded state, and forecast state). Mirrors GET /api/accounts/:accountId/budgets. A budget carries its own `currency` (budgets are NOT converted to the USD base the cost tools return), and `amount_cents` is denominated in it; `spend_cents`/`projected_cents` are in `status_currency`, the budget's currency as of the rollup that wrote them. Never quote any of these figures as dollars without checking those two fields.

### `list_alert_channels` (~54 tokens)

List this account's alert notification channels (Slack/Teams/webhook/email) — need a channel's id to call create_alert_subscription. Never returns the channel's credentials/URL, only its id/type/name/enabled state.

### `list_alert_subscriptions` (~51 tokens)

List which alert channels are subscribed to which trigger (a specific budget's spend_threshold, or account-wide event_overage/cost_anomaly). Mirrors GET /api/accounts/:accountId/alert-subscriptions.

### `list_alert_deliveries` (~85 tokens)

List recent alert delivery history for this account (did an alert actually fire, and did it send successfully) — the same data behind the Alerts page's delivery heatmap. Does not include the delivery error text. Mirrors GET /api/accounts/:accountId/alert-deliveries.

Input parameters:

- `limit` (integer): Max rows, most recent first (default: 100)

### `list_dimensions` (~94 tokens)

List the distinct values seen for a given dimension (service, region, linked_account, usage_type, or operation) for one provider — useful for discovering filter values before calling query_costs.

Input parameters:

- `cost_source_id` (string, required): Provider id, e.g. "aws" — must be enabled for this account
- `dimension` (string, required)
- `end_date` (string)
- `start_date` (string)

### `get_cost_entries` (~181 tokens)

Fetch raw per-service cost entries for this account over a date range (unaggregated). Prefer query_costs for time-bucketed/aggregated spend — this is for inspecting individual rows. Each row's `cost` is in USD (see the response's top-level `currency` field), like every other figure this server returns. A row also carries `native_cost`/`native_currency` — what the provider actually billed, for reconciling against their invoice. Those are the one exception to the USD rule here: never sum or compare `native_cost` across rows, and never quote it without naming the row's `native_currency`. Unlike query_costs, there is no cost_metric parameter here — `cost` is always billed cost, never amortized.

Input parameters:

- `endDate` (string)
- `startDate` (string)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-plutus-cloud-plutus-cost-data/api-mcp#diagnostics

## Score history

- 2026-09-20: 90
- 2026-09-19: 89
- 2026-09-18: 89
- 2026-09-17: 88
- 2026-09-16: 80
- 2026-09-15: 87
- 2026-09-14: 87
- 2026-09-13: 86
- 2026-09-12: 86
- 2026-09-11: 86
- 2026-09-10: 85
- 2026-09-09: 85
- 2026-09-08: 84
- 2026-09-07: 84
- 2026-09-06: 83
- 2026-09-05: 83
- 2026-09-04: 82
- 2026-09-03: 82
- 2026-09-02: 81
- 2026-09-01: 81
- 2026-08-31: 80

## Common questions

### What is the Plutus MCP server?

Plutus is an MCP server listed in the public MCP registry as com.plutus-cloud/plutus-cost-data. Query cloud, AI and SaaS spend across 25+ providers: costs, budgets, anomalies, unit economics. This page covers its hosted endpoint (https://console.plutus-cloud.com/api/mcp).

### Is the Plutus MCP server safe to use?

Plutus scores 90 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the Plutus MCP server expose?

Plutus exposes 31 tools: list_cost_sources, query_costs, list_savings_recommendations, list_commitment_utilization, list_commitment_expirations, and 26 more. Their descriptions and schemas cost roughly 6,356 tokens of context every time the server is loaded.

### Does the Plutus MCP server require authentication?

Yes. Plutus asked us for credentials when we connected, so you will need to authorise it in your MCP client before it can do anything.

### Is the Plutus MCP server still maintained?

Plutus is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://console.plutus-cloud.com/api/mcp
- Website: https://plutus-cloud.com/mcp
- Changelog RSS feed: https://verifymcp.io/servers/com-plutus-cloud-plutus-cost-data/api-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-plutus-cloud-plutus-cost-data/api-mcp.json
- HTML version of this page: https://verifymcp.io/servers/com-plutus-cloud-plutus-cost-data/api-mcp