feat(tools): Support errors dataset and outcome/reason filters in find_dropped_events

Mirrors two backend changes to the events-dropped endpoint:
- errors dataset now maps to DataCategory.ERROR, so add it to the tool's
  dataset enum alongside spans/logs/metrics.
- outcome (closed set of drop classifications) and reason (open sub-class)
  optionally scope the dropped side; accepted volume is always returned in full.

getDroppedEvents forwards both filters; tool exposes them as optional params.

Refs DAIN-1863

Author: manessaraj

packages/mcp-core/src/api-client/client.ts

@@ -5222,6 +5222,8 @@ export class SentryApiService {
       statsPeriod,
       start,
       end,
+      outcome,
+      reason,
     }: {
       organizationSlug: string;
       interval?: string;
@@ -5230,6 +5232,8 @@ export class SentryApiService {
       statsPeriod?: string;
       start?: string;
       end?: string;
+      outcome?: string;
+      reason?: string;
     },
     opts?: RequestOptions,
   ) {
@@ -5242,6 +5246,12 @@ export class SentryApiService {
     if (projectId) {
       queryParams.set("project", projectId);
     }
+    if (outcome) {
+      queryParams.set("outcome", outcome);
+    }
+    if (reason) {
+      queryParams.set("reason", reason);
+    }
     queryParams.set("referrer", SENTRY_MCP_SEARCH_EVENTS_REFERRER);
 
     const apiUrl =

packages/mcp-core/src/skillDefinitions.json

@@ -19,7 +19,7 @@
       },
       {
         "name": "find_dropped_events",
-        "description": "Find events dropped before they were stored in Sentry — ground-truth data-fidelity information about what was and wasn't captured.\n\nEvents can be dropped client-side in the SDK (sample_rate, before_send) or\nserver-side at ingest (rate limited, over quota, filtered, invalid, abuse/spike\nprotection, cardinality limited). Accepted-only views (searches, aggregates,\ncharts) can't show this, so the data may be incomplete in ways they don't reveal\n— for example, a flat or spiky chart caused entirely by drops.\n\nUse this tool when you need to:\n- Explain why a chart is flat, lower than expected, or doesn't match what the user is sending\n- Confirm the data you need is actually in Sentry (not dropped) before trusting a query, aggregate, or dashboard\n- Attribute a volume anomaly to a specific drop reason (quota, spike protection, sampling, filters)\n- Tell the user why their data is missing and what to do about it (raise quota, fix sampling, etc.)\n\nReturns dropped event volume bucketed over time, with the drop `outcome` and `reason`\nfor each bucket, plus the accepted volume per bucket so you can compute the dropped share.\n\n<examples>\nfind_dropped_events(organizationSlug='my-org', dataset='spans', projectSlug='my-project')\nfind_dropped_events(organizationSlug='my-org', dataset='logs', statsPeriod='30d')\n</examples>\n\n<hints>\n- This is independent of any search query — it reports drops for the whole project/time range.\n- `outcome` is the drop kind (e.g. rate_limited, filtered); `reason` is the sub-cause (e.g. key_quota, sample_rate).\n- An empty `droppedEvents` list means no drops in the window — the data can be trusted.\n</hints>",
+        "description": "Find events dropped before they were stored in Sentry — ground-truth data-fidelity information about what was and wasn't captured.\n\nEvents can be dropped client-side in the SDK (sample_rate, before_send) or\nserver-side at ingest (rate limited, over quota, filtered, invalid, abuse/spike\nprotection, cardinality limited). Accepted-only views (searches, aggregates,\ncharts) can't show this, so the data may be incomplete in ways they don't reveal\n— for example, a flat or spiky chart caused entirely by drops.\n\nUse this tool when you need to:\n- Explain why a chart is flat, lower than expected, or doesn't match what the user is sending\n- Confirm the data you need is actually in Sentry (not dropped) before trusting a query, aggregate, or dashboard\n- Attribute a volume anomaly to a specific drop reason (quota, spike protection, sampling, filters)\n- Tell the user why their data is missing and what to do about it (raise quota, fix sampling, etc.)\n\nReturns dropped event volume bucketed over time, with the drop `outcome` and `reason`\nfor each bucket, plus the accepted volume per bucket so you can compute the dropped share.\n\n<examples>\nfind_dropped_events(organizationSlug='my-org', dataset='spans', projectSlug='my-project')\nfind_dropped_events(organizationSlug='my-org', dataset='logs', statsPeriod='30d')\nfind_dropped_events(organizationSlug='my-org', dataset='errors', outcome='rate_limited')\n</examples>\n\n<hints>\n- This is independent of any search query — it reports drops for the whole project/time range.\n- `outcome` is the drop kind (e.g. rate_limited, filtered); `reason` is the sub-cause (e.g. key_quota, sample_rate).\n- Pass `outcome` and/or `reason` to scope the dropped side to one classification; the accepted volume is always returned in full.\n- An empty `droppedEvents` list means no drops in the window — the data can be trusted.\n</hints>",
         "requiredScopes": ["event:read"]
       },
       {

packages/mcp-core/src/toolDefinitions.json

@@ -2223,7 +2223,7 @@
   },
   {
     "name": "find_dropped_events",
-    "description": "Find events dropped before they were stored in Sentry — ground-truth data-fidelity information about what was and wasn't captured.\n\nEvents can be dropped client-side in the SDK (sample_rate, before_send) or\nserver-side at ingest (rate limited, over quota, filtered, invalid, abuse/spike\nprotection, cardinality limited). Accepted-only views (searches, aggregates,\ncharts) can't show this, so the data may be incomplete in ways they don't reveal\n— for example, a flat or spiky chart caused entirely by drops.\n\nUse this tool when you need to:\n- Explain why a chart is flat, lower than expected, or doesn't match what the user is sending\n- Confirm the data you need is actually in Sentry (not dropped) before trusting a query, aggregate, or dashboard\n- Attribute a volume anomaly to a specific drop reason (quota, spike protection, sampling, filters)\n- Tell the user why their data is missing and what to do about it (raise quota, fix sampling, etc.)\n\nReturns dropped event volume bucketed over time, with the drop `outcome` and `reason`\nfor each bucket, plus the accepted volume per bucket so you can compute the dropped share.\n\n<examples>\nfind_dropped_events(organizationSlug='my-org', dataset='spans', projectSlug='my-project')\nfind_dropped_events(organizationSlug='my-org', dataset='logs', statsPeriod='30d')\n</examples>\n\n<hints>\n- This is independent of any search query — it reports drops for the whole project/time range.\n- `outcome` is the drop kind (e.g. rate_limited, filtered); `reason` is the sub-cause (e.g. key_quota, sample_rate).\n- An empty `droppedEvents` list means no drops in the window — the data can be trusted.\n</hints>",
+    "description": "Find events dropped before they were stored in Sentry — ground-truth data-fidelity information about what was and wasn't captured.\n\nEvents can be dropped client-side in the SDK (sample_rate, before_send) or\nserver-side at ingest (rate limited, over quota, filtered, invalid, abuse/spike\nprotection, cardinality limited). Accepted-only views (searches, aggregates,\ncharts) can't show this, so the data may be incomplete in ways they don't reveal\n— for example, a flat or spiky chart caused entirely by drops.\n\nUse this tool when you need to:\n- Explain why a chart is flat, lower than expected, or doesn't match what the user is sending\n- Confirm the data you need is actually in Sentry (not dropped) before trusting a query, aggregate, or dashboard\n- Attribute a volume anomaly to a specific drop reason (quota, spike protection, sampling, filters)\n- Tell the user why their data is missing and what to do about it (raise quota, fix sampling, etc.)\n\nReturns dropped event volume bucketed over time, with the drop `outcome` and `reason`\nfor each bucket, plus the accepted volume per bucket so you can compute the dropped share.\n\n<examples>\nfind_dropped_events(organizationSlug='my-org', dataset='spans', projectSlug='my-project')\nfind_dropped_events(organizationSlug='my-org', dataset='logs', statsPeriod='30d')\nfind_dropped_events(organizationSlug='my-org', dataset='errors', outcome='rate_limited')\n</examples>\n\n<hints>\n- This is independent of any search query — it reports drops for the whole project/time range.\n- `outcome` is the drop kind (e.g. rate_limited, filtered); `reason` is the sub-cause (e.g. key_quota, sample_rate).\n- Pass `outcome` and/or `reason` to scope the dropped side to one classification; the accepted volume is always returned in full.\n- An empty `droppedEvents` list means no drops in the window — the data can be trusted.\n</hints>",
     "inputSchema": {
       "type": "object",
       "properties": {
@@ -2246,7 +2246,7 @@
         "dataset": {
           "default": "spans",
           "type": "string",
-          "enum": ["spans", "logs", "metrics"],
+          "enum": ["spans", "logs", "metrics", "errors"],
           "description": "Which data type to report drops for."
         },
         "projectSlug": {
@@ -2308,6 +2308,38 @@
               "type": "null"
             }
           ]
+        },
+        "outcome": {
+          "default": null,
+          "anyOf": [
+            {
+              "type": "string",
+              "enum": [
+                "rate_limited",
+                "filtered",
+                "invalid",
+                "abuse",
+                "client_discard",
+                "cardinality_limited"
+              ],
+              "description": "Scope the dropped side to one top-level drop classification. Accepted volume is still returned in full."
+            },
+            {
+              "type": "null"
+            }
+          ]
+        },
+        "reason": {
+          "default": null,
+          "anyOf": [
+            {
+              "type": "string",
+              "description": "Scope the dropped side to one reason (sub-classification within an outcome, e.g. 'spike_protection'). Combine with `outcome`."
+            },
+            {
+              "type": "null"
+            }
+          ]
         }
       },
       "required": ["organizationSlug"]

packages/mcp-core/src/tools/catalog/find-dropped-events.test.ts

@@ -67,6 +67,8 @@ describe("find_dropped_events", () => {
         start: null,
         end: null,
         interval: null,
+        outcome: null,
+        reason: null,
       },
       context,
     );
@@ -104,4 +106,37 @@ describe("find_dropped_events", () => {
       }
     `);
   });
+
+  it("forwards the errors dataset and outcome/reason filters to the API", async () => {
+    let captured: URLSearchParams | undefined;
+    mswServer.use(
+      http.get(
+        "https://sentry.io/api/0/organizations/sentry-mcp-evals/events-dropped/",
+        ({ request }) => {
+          captured = new URL(request.url).searchParams;
+          return HttpResponse.json(DROPPED_EVENTS_RESPONSE);
+        },
+      ),
+    );
+
+    await findDroppedEvents.handler(
+      {
+        organizationSlug: "sentry-mcp-evals",
+        regionUrl: null,
+        dataset: "errors",
+        projectSlug: null,
+        statsPeriod: "24h",
+        start: null,
+        end: null,
+        interval: null,
+        outcome: "rate_limited",
+        reason: "spike_protection",
+      },
+      context,
+    );
+
+    expect(captured?.get("dataset")).toBe("errors");
+    expect(captured?.get("outcome")).toBe("rate_limited");
+    expect(captured?.get("reason")).toBe("spike_protection");
+  });
 });

packages/mcp-core/src/tools/catalog/find-dropped-events.ts

@@ -10,7 +10,16 @@ import {
 import { setTargetTagsAndAttributes } from "../../telem/scope";
 import type { ServerContext } from "../../types";
 
-const DROPPED_EVENTS_DATASETS = ["spans", "logs", "metrics"] as const;
+const DROPPED_EVENTS_DATASETS = ["spans", "logs", "metrics", "errors"] as const;
+
+const DROP_OUTCOMES = [
+  "rate_limited",
+  "filtered",
+  "invalid",
+  "abuse",
+  "client_discard",
+  "cardinality_limited",
+] as const;
 
 const droppedBucketSchema = z.object({
   outcome: z.string(),
@@ -53,11 +62,13 @@ export default defineTool({
     "<examples>",
     "find_dropped_events(organizationSlug='my-org', dataset='spans', projectSlug='my-project')",
     "find_dropped_events(organizationSlug='my-org', dataset='logs', statsPeriod='30d')",
+    "find_dropped_events(organizationSlug='my-org', dataset='errors', outcome='rate_limited')",
     "</examples>",
     "",
     "<hints>",
     "- This is independent of any search query — it reports drops for the whole project/time range.",
     "- `outcome` is the drop kind (e.g. rate_limited, filtered); `reason` is the sub-cause (e.g. key_quota, sample_rate).",
+    "- Pass `outcome` and/or `reason` to scope the dropped side to one classification; the accepted volume is always returned in full.",
     "- An empty `droppedEvents` list means no drops in the window — the data can be trusted.",
     "</hints>",
   ].join("\n"),
@@ -97,6 +108,21 @@ export default defineTool({
       )
       .nullable()
       .default(null),
+    outcome: z
+      .enum(DROP_OUTCOMES)
+      .describe(
+        "Scope the dropped side to one top-level drop classification. Accepted volume is still returned in full.",
+      )
+      .nullable()
+      .default(null),
+    reason: z
+      .string()
+      .trim()
+      .describe(
+        "Scope the dropped side to one reason (sub-classification within an outcome, e.g. 'spike_protection'). Combine with `outcome`.",
+      )
+      .nullable()
+      .default(null),
   },
   annotations: {
     readOnlyHint: true,
@@ -132,6 +158,8 @@ export default defineTool({
       statsPeriod: params.statsPeriod ?? undefined,
       start: params.start ?? undefined,
       end: params.end ?? undefined,
+      outcome: params.outcome ?? undefined,
+      reason: params.reason ?? undefined,
     });
 
     const toBucket = (bucket: {