mcp-gtm-signals-aggregator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| APIFY_TOKEN | Yes | Your Apify API token |
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 |
|---|---|
| aggregate_gtm_signalsA | Aggregate a company's GTM signals into one composite score. Runs hiring-signal and tech-stack detection in a single call and returns a flat, Clay-ready JSON row with a composite GTM score, a recommended action, and an optional plain-English summary. Read-only; requires an APIFY_TOKEN and consumes Apify credits per call. |
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
With only one tool in the set, there is no possibility of an agent confusing it with another tool. Its purpose—producing a composite GTM score plus recommended action—is stated unambiguously.
The single name aggregate_gtm_signals follows a clean verb_noun snake_case convention that would scale predictably. Consistency cannot be fully demonstrated across a set of one, so it falls just short of a 5.
A single tool is borderline thin for a server branded as a 'signals aggregator'; the composite design is defensible, but there is no surface for retrieving individual signals, batching companies, or inspecting components.
The one-tool surface covers the headline aggregation use case end-to-end, but it is read-only and monolithic, leaving no way to access raw hiring/tech-stack signals, batch multiple companies, or tune scoring inputs.