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Facebook_ads

by io.github.pipeworx-io

Fb Campaign Insights

fb_campaign_insights
Read-onlyIdempotent

Get campaign performance metrics: impressions, clicks, spend, CTR, CPC, conversions, ROAS. Requires account_id and campaign_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoComma-separated metrics (default: "impressions,clicks,spend,ctr,cpc,cpm,reach,actions")
campaign_idYesCampaign ID
date_presetNoDate preset (e.g., "today", "yesterday", "last_7d", "last_30d", "this_month")
time_range_sinceNoStart date YYYY-MM-DD (use instead of date_preset)
time_range_untilNoEnd date YYYY-MM-DD (use with time_range_since)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoPerformance metrics rows
errorNoError code if connection failed
pagingNoPagination info
messageNoError message if connection failed

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "data": {
+      "description": "Performance metrics rows",
+      "items": {
+        "properties": {
+          "actions": {
+            "description": "Action breakdowns",
+            "type": "array"
+          },
+          "clicks": {
+            "description": "Total clicks",
+            "type": "string"
+          },
+          "cpc": {
+            "description": "Cost per click",
+            "type": "string"
+          },
+          "cpm": {
+            "description": "Cost per thousand impressions",
+            "type": "string"
+          },
+          "ctr": {
+            "description": "Click-through rate percentage",
+            "type": "string"
+          },
+          "date_start": {
+            "description": "Start date YYYY-MM-DD",
+            "type": "string"
+          },
+          "date_stop": {
+            "description": "End date YYYY-MM-DD",
+            "type": "string"
+          },
+          "impressions": {
+            "description": "Total impressions",
+            "type": "string"
+          },
+          "reach": {
+            "description": "Unique people reached",
+            "type": "string"
+          },
+          "spend": {
+            "description": "Total spend in account currency",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "error": {
+      "description": "Error code if connection failed",
+      "type": "string"
+    },
+    "message": {
+      "description": "Error message if connection failed",
+      "type": "string"
+    },
+    "paging": {
+      "description": "Pagination info",
+      "properties": {
+        "cursors": {
+          "type": "object"
+        },
+        "next": {
+          "type": "string"
+        }
+      },
+      "type": "object"
+    }
+  },
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "campaign_id": "120393847102340",
+    "date_preset": "last_7d"
+  },
+  {
+    "campaign_id": "120393847102340",
+    "fields": "impressions,clicks,spend,ctr,cpc,cpm,reach,actions,action_values",
+    "time_range_since": "2024-01-01",
+    "time_range_until": "2024-01-31"
+  }
+]
  3. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the agent knows this is a safe, read-only operation. The description adds no new behavioral context beyond listing metrics. It does not contradict annotations, but the erroneous 'account_id' requirement could confuse the agent about parameter usage. Score 3 because annotations carry the burden.

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?

The description is two sentences and adequately front-loaded with verb and resource. However, the spurious 'account_id' adds noise. Most information is useful, but the error detracts from conciseness. Still, it is appropriately sized for the tool's complexity.

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

Completeness3/5

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

Given the output schema exists (which explains return values), the description covers basic functionality. It lists examples of metrics but omits cpm, reach, actions, action_values mentioned in schema. It does not explain date_preset vs time_range usage. The incorrect parameter again weakens completeness. Adequate but not thorough.

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

Parameters2/5

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

Schema coverage is 100% with descriptions for all 5 parameters, so the description adds minimal value. It mentions 'account_id' (not in schema) and 'campaign_id', but does not explain date_preset/time_range interplay or default metrics. The incorrect parameter reduces trust. Baseline 3 reduced to 2 due to inaccuracy.

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?

The description clearly states the verb 'Get' and identifies the resource as 'campaign performance metrics'. It lists specific metrics (impressions, clicks, spend, etc.), distinguishing it from siblings like fb_get_campaign (which likely returns campaign details) and fb_list_campaigns (which lists campaigns but not metrics).

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

Usage Guidelines2/5

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

The description mentions required parameters but does not provide guidance on when to use this tool versus alternatives. It lacks explicit when-not or context for selection, and contains an inaccuracy: it claims 'account_id' is required, but the input schema only requires 'campaign_id'. This misstatement reduces clarity for the agent.

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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TDQS

A3.6/5.0
Disambiguation4/5

The 11 fb_* Facebook tools are clearly separated by resource (account vs campaign vs adset) and action (list vs get vs create), and the Pipeworx research tools each have distinct roles (router, grounded, profile, compare, research). However, ask_pipeworx, ask_pipeworx_beta, and deep_research overlap in routing/fan-out behavior, and ai_visibility_check vs scan_competitor_ai_presence are near-identical in purpose, creating some ambiguity.

Naming Consistency3/5

The 11 fb_* tools follow a consistent fb_verb_noun pattern (except fb_get_campaign vs fb_list_*), but the remaining 25+ tools mix verb-first (ask_pipeworx, compare_entities, resolve_entity), noun-first (entity_profile, recent_changes, polymarket_edges), and generic names (forget, recall, remember). Pipeworx tools use verb_noun mostly consistently (ask_pipeworx, discover_tools, resolve_entity) but the overall set blends two naming cultures without a unifying prefix or pattern.

Tool Count3/5

36 tools is on the heavy side for one server. The Facebook ads domain only needs ~11 tools, while the rest are a sprawling Pipeworx research/meta platform (memory, subscription, prediction-market, web-tooling, AI-visibility) that feels like several servers merged into one. Each area is internally coherent, but as a single MCP server the count is bloated.

Completeness4/5

The Facebook ads surface covers list accounts/campaigns/adsets and read campaigns/insights, but notably lacks create/update/delete operations for campaigns and adsets, so the ad-management workflow has dead ends. The Pipeworx research side is extremely complete for data lookup (router, grounded, deep research, entity profiles, comparisons, verification), though the memory/subscription tools introduce a separate domain that is only thinly supported.

Resources