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Glama

Facebook_ads

by io.github.pipeworx-io

Fb Get Campaign

fb_get_campaign
Read-onlyIdempotent

Get detailed campaign info: name, budget, status, schedule, and targeting. Requires account_id and campaign_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoComma-separated fields (default: "id,name,status,objective,daily_budget,lifetime_budget,start_time,stop_time,created_time,updated_time")
campaign_idYesCampaign ID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoCampaign ID
nameNoCampaign name
errorNoError code if connection failed
statusNoCampaign status
messageNoError message if connection failed
objectiveNoCampaign objective
stop_timeNoCampaign stop time ISO 8601
start_timeNoCampaign start time ISO 8601
created_timeNoCampaign creation time ISO 8601
daily_budgetNoDaily budget in cents
updated_timeNoCampaign last update time ISO 8601
lifetime_budgetNoLifetime budget in cents

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": {
+    "created_time": {
+      "description": "Campaign creation time ISO 8601",
+      "type": "string"
+    },
+    "daily_budget": {
+      "description": "Daily budget in cents",
+      "type": "number"
+    },
+    "error": {
+      "description": "Error code if connection failed",
+      "type": "string"
+    },
+    "id": {
+      "description": "Campaign ID",
+      "type": "string"
+    },
+    "lifetime_budget": {
+      "description": "Lifetime budget in cents",
+      "type": "number"
+    },
+    "message": {
+      "description": "Error message if connection failed",
+      "type": "string"
+    },
+    "name": {
+      "description": "Campaign name",
+      "type": "string"
+    },
+    "objective": {
+      "description": "Campaign objective",
+      "type": "string"
+    },
+    "start_time": {
+      "description": "Campaign start time ISO 8601",
+      "type": "string"
+    },
+    "status": {
+      "description": "Campaign status",
+      "type": "string"
+    },
+    "stop_time": {
+      "description": "Campaign stop time ISO 8601",
+      "type": "string"
+    },
+    "updated_time": {
+      "description": "Campaign last update time ISO 8601",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "campaign_id": "120393847102340"
+  },
+  {
+    "campaign_id": "120393847102340",
+    "fields": "id,name,status,objective,daily_budget,lifetime_budget,start_time,stop_time,created_time,updated_time,adset_spec"
+  }
+]
  3. First observed

TDQS

C2.6/5.0
Behavior2/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which are consistent with a read operation. However, the description claims it 'Requires account_id and campaign_id', while the schema only requires campaign_id. This inaccuracy reduces transparency and could mislead an agent.

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

Conciseness3/5

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

The description is a single, concise sentence. However, it includes an inaccuracy (account_id requirement). It is front-loaded with purpose but lacks structure and precision.

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

Completeness2/5

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

Given that an output schema exists and annotations cover safety, the description should add usage context, such as when to retrieve detailed info vs insights. It does not explain the return value structure or differentiate from sibling tools, leaving the agent under-informed.

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%, so parameters are documented. The description adds no semantic value beyond the schema; it incorrectly states that account_id is required, and the mention of 'targeting' in returned fields is not reflected in the schema's default fields list.

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

Purpose4/5

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

The description clearly states the verb 'Get' and the resource 'detailed campaign info', listing specific fields like name, budget, status, schedule, and targeting. However, it does not distinguish this tool from sibling tools like fb_campaign_insights or fb_list_campaigns, which could also retrieve campaign data.

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?

No guidance on when to use this tool versus alternatives. The sibling list includes fb_campaign_insights (for metrics) and fb_list_campaigns (for listing), but the description does not clarify that this tool is for detailed configuration info.

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