Infer a GTM stack from a freeform text blob (a careers page, job posting, public site HTML, RFP, 'What we use' doc, browser DevTools network tab, etc.). Returns ranked tool matches with confidence levels (high/medium/low) and evidence snippets, plus a ready-to-use array for chaining into scan_sta...
AI agents call detect_stack_from_text to retrieve information from StackSwap without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
text | string | Yes | The text to scan. Anything from a job post to raw HTML works. Max 50KB. |
Parameters from the server's own tool schema.
This tool performs text analysis and pattern matching to classify software tools mentioned in documents (careers pages, job postings, etc.). It retrieves and correlates information without modifying any data, executing code, or triggering external side effects. The returned matches are informational only and designed to be inputs to downstream analysis tools.
From the tool's definition Tool description states it 'infer[s]' and 'returns ranked tool matches' from text analysis. The description emphasizes read-only operations: parsing text blobs, matching against known tools, and returning data for 'chaining into' other tools.
Attacks that exploit this kind of access
Infer a GTM stack from a freeform text blob (a careers page, job posting, public site HTML, RFP, 'What we use' doc, browser DevTools network tab, etc.). Returns ranked tool matches with confidence levels (high/medium/low) and evidence snippets, plus a ready-to-use array for chaining into scan_stack or find_overlaps. Use when the user says 'I don't know what we use' or pastes a competitor's careers page to scout. Conservative on ambiguous short tokens — multi-mention or canonical-name matches win. It is categorised as a Read tool in the StackSwap MCP Server, which means it retrieves data without modifying state.
detect_stack_from_text accepts 1 parameter: text. Required: text. The full parameter table on this page comes from the server's own tool schema.
Register the StackSwap MCP server in PolicyLayer and add a rule for detect_stack_from_text: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches StackSwap. Nothing to install.
detect_stack_from_text is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the detect_stack_from_text rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for detect_stack_from_text. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
detect_stack_from_text is provided by the StackSwap MCP server (StonesofCreation/stackswap-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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