AI Answer Visibility Tracker MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| APIFY_TOKEN | Yes | Your Apify API token from console.apify.com/account/integrations. Required for tool calls; the server can list its tool without it. | |
| GEMINI_API_KEY | No | Optional Google AI Studio/Gemini API key to ask Gemini as an engine. Billed to you by Google. | |
| OPENAI_API_KEY | No | Optional OpenAI API key to ask ChatGPT as an engine. Billed to you by OpenAI. | |
| ANTHROPIC_API_KEY | No | Optional Anthropic API key to ask Claude as an engine. Billed to you by Anthropic. | |
| PERPLEXITY_API_KEY | No | Optional Perplexity API key to ask Perplexity as an engine. Billed to you by Perplexity. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| track_ai_answer_visibilityA | Check whether AI answers name and cite a brand for the questions its buyers ask. Give brand_name, brand_domain, and questions (for example "best crm for small business"). Each question is asked samples times (default 3) on each engine: google_ai_overview needs no key; openai (ChatGPT), anthropic (Claude), perplexity, and gemini run on the caller's own API keys, which this server reads from its environment (OPENAI_API_KEY, ANTHROPIC_API_KEY, PERPLEXITY_API_KEY, GEMINI_API_KEY). Returns one sample row per answer (brand_named, brand_cited, first_mention_rank, competitors_named, cited_domains, answer_excerpt), one question_summary row per question and engine (brand_named_rate, brand_cited_rate with a 95 percent range, top_cited_domains, competitor rates), and one free brand_summary row per engine. Bad input returns one free row whose error_reason starts with input_invalid. A run that does not succeed is returned as an error with its run ID. Read-only; requires an APIFY_TOKEN; Apify charges per Google sample, per engine sample, and per question rates row. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 1 tool
There is only one tool, so there is no possibility of tool-selection confusion. Its purpose is clearly scoped to checking AI answer visibility for a brand across questions and engines.
The single tool uses a clear snake_case verb_noun pattern: track_ai_answer_visibility. With only one tool, there are no competing conventions or naming inconsistencies.
A single tool is reasonable for a focused visibility-tracking operation, and it avoids unnecessary surface area. However, the one tool bundles many engines, sampling, and summary outputs, so 1 tool is on the thin side and could arguably be split into more granular operations.
The tool covers the core domain well: multi-engine querying, sampling, per-answer rows, per-question summaries, per-brand summaries, and input/error handling. Minor gaps remain around retrieving prior runs by run ID or managing historical visibility comparisons, but the main workflow is complete.