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Glama

Facebook_ads

by io.github.pipeworx-io

Fb List Campaigns

fb_list_campaigns
Read-onlyIdempotent

List campaigns in a Facebook ad account (e.g., account_id: '123456789'). Returns campaign names, IDs, status, and objectives.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 25)
fieldsNoComma-separated fields (default: "id,name,status,objective,daily_budget,lifetime_budget")
act_account_idYesAd account ID with act_ prefix (e.g., "act_123456789")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoList of campaigns
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": "List of campaigns",
+      "items": {
+        "properties": {
+          "daily_budget": {
+            "description": "Daily budget in cents",
+            "type": "number"
+          },
+          "id": {
+            "description": "Campaign ID",
+            "type": "string"
+          },
+          "lifetime_budget": {
+            "description": "Lifetime budget in cents",
+            "type": "number"
+          },
+          "name": {
+            "description": "Campaign name",
+            "type": "string"
+          },
+          "objective": {
+            "description": "Campaign objective",
+            "type": "string"
+          },
+          "status": {
+            "description": "Campaign status",
+            "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: +[
+  {
+    "act_account_id": "act_123456789"
+  },
+  {
+    "act_account_id": "act_987654321",
+    "fields": "id,name,status,objective,daily_budget,lifetime_budget,created_time",
+    "limit": 50
+  }
+]
  3. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds context on return fields (names, IDs, status, objectives), which is helpful. Does not contradict annotations.

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?

Single sentence with an example; concise and front-loaded. Could add more structure but no unnecessary content.

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

Completeness4/5

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

With full schema coverage, annotations, and an output schema (not provided but exists), the description is adequate for a listing tool. It covers key return fields and usage context.

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

Parameters3/5

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

Schema coverage is 100% with full parameter descriptions. The description only adds a usage example for act_account_id format, adding minimal meaning beyond the schema. Baseline 3 is appropriate.

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?

Clearly states the tool lists campaigns in a Facebook ad account, specifying the verb 'list' and the resource 'campaigns in a Facebook ad account'. Distinguishes from sibling tools like fb_get_campaign (single campaign) and fb_campaign_insights (insights).

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

Usage Guidelines4/5

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

Provides an example of usage with account_id format, implying context. However, does not explicitly state when to use versus alternatives or when not to use it. Sibling tool names provide implicit differentiation.

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