SEO GSC Wizard MCP

Forecast organic traffic

forecast_traffic

Read-only

Use this when the user asks how much search traffic to expect in coming weeks or months. Projects future Search Console clicks (or impressions) for a property using the app's forecasting model: multiplicative seasonal decomposition (ratio-to-moving-average) plus an auto-selected trendline (linear / polynomial / log / exponential / power by best R-squared), re-seasonalised for each future period. Not for explaining a past change: use detect_change_points. forecast runs oldest period first, candidateTrendlines best r2 first; *Sessions fields count the chosen metric (clicks or impressions). Optionally applies a manual growth rate and derives revenue from a conversion rate and average order value. History needs: weekly needs 13 complete weeks and monthly 6 complete months, after the first and last (possibly partial) period are dropped, so about 105 days (weekly) or 240 days (monthly) of data. Days and periods without rows count as zero. A constant history (for example all zero) gets a flat forecast with forecastNote. Reads the ClickHouse warehouse when available, else the live Search Console API.

Input Schema

Name	Required	Description	Default
`aov`	No	Optional average order value (in currency units) used with cvr for revenue.
`cvr`	No	Optional conversion rate as a decimal (0.025 = 2.5%) to derive forecast revenue.
`metric`	No	Metric to forecast (treated as "sessions" by the model).	clicks
`siteUrl`	Yes
`currency`	No	Currency label for the revenue fields (display only).	USD
`growthRate`	No	Optional manual growth rate per period as a decimal (0.05 = +5%). Default 0.
`granularity`	No	Forecast granularity. Weekly needs about 105 days of history (13 complete weeks), monthly about 240 days (6 complete months).	weekly
`historyDays`	No	Trailing days of history to fit on (default 480 ≈ 16 months; more improves seasonality).
`trendlineType`	No	Force a trendline model, or "auto" for the best R-squared (default).	auto
`compoundGrowth`	No	Compound the growth rate across periods (default true).
`forecastPeriods`	No	How many future periods (weeks or months) to project. Default 26.
`additionalSessions`	No	Optional flat sessions added to every forecast period. Default 0.

Output Schema

Name	Required	Description
`note`	No
`metric`	No
`thenBy`	No
`listKey`	No	Name of the top-level field that holds the rows sortedBy describes.
`siteUrl`	No
`warning`	No
`currency`	No
`forecast`	No
`ordering`	No
`sortedBy`	No
`sortOrder`	No
`thenOrder`	No
`trendline`	No
`dataSource`	No
`granularity`	No
`partialDays`	No
`dataMaturity`	No
`forecastNote`	No
`historyRange`	No
`settledThrough`	No
`seasonalIndices`	No
`historicalPeriods`	No
`candidateTrendlines`	No
`warehouseLatestDate`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 28, 2026

addedOutput schema / properties / listKey

Added value: +{
+  "$ref": "#/properties/siteUrl",
+  "description": "Name of the top-level field that holds the rows sortedBy describes."
+}

Changed13 schema fields changedOct 18, 2026

changedOutput schema / additionalProperties
```
Previous value: -falseNew value: +true
```
changedOutput schema / properties / candidateTrendlines / items / additionalProperties
```
Previous value: -falseNew value: +true
```

changedOutput schema / properties / dataMaturity / anyOf

Previous value: -[
-  {
-    "additionalProperties": false,
-    "properties": {
-      "dateBasis": {
-        "$ref": "#/properties/siteUrl"
-      },
-      "firstIncompleteDate": {
-        "$ref": "#/properties/siteUrl"
-      },
-      "note": {
-        "$ref": "#/properties/siteUrl"
-      },
-      "probe": {
-        "anyOf": [
-          {
-            "additionalProperties": false,
-            "properties": {
-              "dataState": {
-                "$ref": "#/properties/siteUrl"
-              },
-              "endDate": {
-                "$ref": "#/properties/siteUrl"
-              },
-              "searchType": {
-                "$ref": "#/properties/siteUrl"
-              },
-              "startDate": {
-                "$ref": "#/properties/siteUrl"
-              }
-            },
-            "type": "object"
-          },
-          {
-            "type": "null"
-          }
-        ]
-      },
-      "settledThrough": {
-        "$ref": "#/properties/siteUrl"
-      },
-      "source": {
-        "$ref": "#/properties/siteUrl"
-      },
-      "warehouseCutoff": {
-        "$ref": "#/properties/siteUrl"
-      }
-    },
-    "type": "object"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "additionalProperties": true,
+    "properties": {
+      "dateBasis": {
+        "$ref": "#/properties/siteUrl"
+      },
+      "firstIncompleteDate": {
+        "$ref": "#/properties/siteUrl"
+      },
+      "note": {
+        "$ref": "#/properties/siteUrl"
+      },
+      "probe": {
+        "anyOf": [
+          {
+            "additionalProperties": true,
+            "properties": {
+              "dataState": {
+                "$ref": "#/properties/siteUrl"
+              },
+              "endDate": {
+                "$ref": "#/properties/siteUrl"
+              },
+              "searchType": {
+                "$ref": "#/properties/siteUrl"
+              },
+              "startDate": {
+                "$ref": "#/properties/siteUrl"
+              }
+            },
+            "type": "object"
+          },
+          {
+            "type": "null"
+          }
+        ]
+      },
+      "settledThrough": {
+        "$ref": "#/properties/siteUrl"
+      },
+      "source": {
+        "$ref": "#/properties/siteUrl"
+      },
+      "warehouseCutoff": {
+        "$ref": "#/properties/siteUrl"
+      }
+    },
+    "type": "object"
+  },
+  {
+    "type": "null"
+  }
+]

changedOutput schema / properties / forecast / items / additionalProperties
```
Previous value: -falseNew value: +true
```

changedOutput schema / properties / historyRange / anyOf

Previous value: -[
-  {
-    "additionalProperties": false,
-    "properties": {
-      "days": {
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "endDate": {
-        "$ref": "#/properties/siteUrl"
-      },
-      "startDate": {
-        "$ref": "#/properties/siteUrl"
-      }
-    },
-    "type": "object"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "additionalProperties": true,
+    "properties": {
+      "days": {
+        "type": [
+          "number",
+          "null"
+        ]
+      },
+      "endDate": {
+        "$ref": "#/properties/siteUrl"
+      },
+      "startDate": {
+        "$ref": "#/properties/siteUrl"
+      }
+    },
+    "type": "object"
+  },
+  {
+    "type": "null"
+  }
+]

addedOutput schema / properties / ordering

Added value: +{
+  "anyOf": [
+    {
+      "additionalProperties": {
+        "additionalProperties": true,
+        "properties": {
+          "sortOrder": {
+            "$ref": "#/properties/siteUrl"
+          },
+          "sortedBy": {
+            "$ref": "#/properties/siteUrl"
+          },
+          "thenBy": {
+            "$ref": "#/properties/siteUrl"
+          },
+          "thenOrder": {
+            "$ref": "#/properties/siteUrl"
+          }
+        },
+        "type": "object"
+      },
+      "type": "object"
+    },
+    {
+      "type": "null"
+    }
+  ]
+}

addedOutput schema / properties / partialDays

Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ]
+}

addedOutput schema / properties / sortOrder

Added value: +{
+  "$ref": "#/properties/siteUrl"
+}

addedOutput schema / properties / sortedBy

Added value: +{
+  "$ref": "#/properties/siteUrl"
+}

addedOutput schema / properties / thenBy

Added value: +{
+  "$ref": "#/properties/siteUrl"
+}

addedOutput schema / properties / thenOrder

Added value: +{
+  "$ref": "#/properties/siteUrl"
+}

changedOutput schema / properties / trendline / anyOf

Previous value: -[
-  {
-    "additionalProperties": false,
-    "properties": {
-      "equation": {
-        "$ref": "#/properties/siteUrl"
-      },
-      "r2": {
-        "$ref": "#/properties/historyRange/anyOf/0/properties/days"
-      },
-      "type": {
-        "$ref": "#/properties/siteUrl"
-      }
-    },
-    "type": "object"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "additionalProperties": true,
+    "properties": {
+      "equation": {
+        "$ref": "#/properties/siteUrl"
+      },
+      "r2": {
+        "$ref": "#/properties/historyRange/anyOf/0/properties/days"
+      },
+      "type": {
+        "$ref": "#/properties/siteUrl"
+      }
+    },
+    "type": "object"
+  },
+  {
+    "type": "null"
+  }
+]

addedOutput schema / properties / warning

Added value: +{
+  "$ref": "#/properties/siteUrl"
+}

Changed3 schema fields changedOct 10, 2026

changedInput schema / properties / granularity / description

Previous value: -"Forecast granularity. Weekly needs >= 13 weeks of history, monthly >= 6 months."New value: +"Forecast granularity. Weekly needs about 105 days of history (13 complete weeks), monthly about 240 days (6 complete months)."

addedOutput schema / properties / forecastNote

Added value: +{
+  "$ref": "#/properties/siteUrl"
+}

addedOutput schema / properties / warehouseLatestDate

Added value: +{
+  "$ref": "#/properties/siteUrl"
+}

First observedOct 7, 2026

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/openWorld/non-destructive, and the description adds substantial context beyond them: the modeling approach, minimum history thresholds with the partial-period dropping rule, zero-filling of missing days/periods, the constant-history flat-forecast edge case with forecastNote, and the warehouse-vs-live-API data source. These are exactly the behaviors an agent cannot get from structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded correctly: use case, exclusion, then mechanics, so an agent can decide before reading the modeling internals. It is dense and near the useful limit — the trendline-algorithm enumeration and R-squared asides add credibility but are more than an agent needs to invoke the tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 12-parameter forecasting tool with an output schema, the description covers the remaining unknowns: history minimums and data-window math, partial-period handling, zero-fill semantics, degenerate-history behavior, and degraded-mode data source. Nothing an agent needs in order to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 92%, so the baseline is 3; the description earns one more by explaining cross-parameter behavior the schema doesn't: growthRate/cvr/aov optionally combine for revenue, metric choice propagates into the *Sessions output fields, and history requirements differ per granularity. Much of the detail (defaults, enums) is redundant with the schema, which keeps it from a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Projects future Search Console clicks (or impressions) for a property") and names the scope (coming weeks/months). It also explicitly separates itself from the closest sibling, detect_change_points, so an agent can route without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Opens with an explicit when-to-use trigger ("user asks how much search traffic to expect in coming weeks or months") and immediately gives a when-not plus the named alternative ("Not for explaining a past change: use detect_change_points"). Both halves of the routing decision are stated, not inferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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