content_discovery
Discover content franchises within a domain. Two modes: pass tag for a precise taxonomy match (every game tagged 'co-op'), or pass query for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag...
This record as markdown: /tools/io-github-getgapup-gapup-mcp/content-discovery.md
What content_discovery does on Gapup Mcp
AI agents call content_discovery to retrieve information from Gapup Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
tag | string | — | Tag label to match precisely (e.g. 'thriller', 'co-op'). Mutually exclusive with `query`. |
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
limit | integer | — | Maximum franchises to return (default 25) |
query | string | — | Free-text intent for semantic search (e.g. 'melancholic synth-pop about heartbreak'). Mutually exclusive with `tag`. |
domain | string | Yes | Content domain to search within |
Parameters from the server's own tool schema.
Why content_discovery is rated Low
This tool performs a search/discovery operation with no side effects. It queries existing data (content franchises, tags, embeddings) and returns results with confidence scores. No data is created, modified, deleted, or overwritten. No code execution or financial operations occur. This is a pure Read operation, low severity due to limited blast radius if misused (information retrieval only).
From the tool's definition 'Discover content franchises within a domain' — retrieves data via tag matching or semantic search. 'Results are verifiable' and 'carry a similarity score' — returns query results. No create, modify, delete, execute, or financial operations mentioned.
Risk signalsAccepts freeform code/query input (query) · Bulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs content_discovery safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gapup Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For content_discovery, this is the rule to start with:
content_discovery is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, apply this rule, and every content_discovery call is checked against it from then on.
Questions about content_discovery
Discover content franchises within a domain. Two modes: pass tag for a precise taxonomy match (every game tagged 'co-op'), or pass query for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query. It is categorised as a Read tool in the Gapup Mcp MCP Server, which means it retrieves data without modifying state.
content_discovery accepts 5 parameters: tag, async, limit, query, domain. Required: domain. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for content_discovery: 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 Gapup Mcp. Nothing to install.
content_discovery 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 content_discovery 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 content_discovery. 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.
content_discovery is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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