content_taxonomy
Return the enrichment taxonomy of a content domain — every tag grouped by facet (genre, theme, mood, play-mode…). When to use this tool: an agent needs the controlled vocabulary to filter, classify or query content. Input: a domain.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/content-taxonomy.md
What content_taxonomy does on Mcp Knowledge
AI agents call content_taxonomy to retrieve information from Mcp Knowledge 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 |
|---|---|---|---|
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 |
domain | string | Yes | Content domain |
Parameters from the server's own tool schema.
Why content_taxonomy is rated Low
This is a pure retrieval operation that queries and returns structured metadata about a content domain. There are no side effects, no data modification, no code execution, and no destructive or financial operations. It serves an informational purpose to support filtering and classification tasks. Low severity because misuse yields only informational exposure with no blast radius for data integrity or system state.
From the tool's definition Tool returns taxonomy/vocabulary data ('Return the enrichment taxonomy'). It retrieves controlled vocabulary grouped by facet (genre, theme, mood, play-mode). No modification, deletion, or execution described.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs content_taxonomy safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For content_taxonomy, this is the rule to start with:
content_taxonomy 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 Mcp Knowledge, apply this rule, and every content_taxonomy call is checked against it from then on.
Questions about content_taxonomy
Return the enrichment taxonomy of a content domain — every tag grouped by facet (genre, theme, mood, play-mode…). When to use this tool: an agent needs the controlled vocabulary to filter, classify or query content. Input: a domain. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.
content_taxonomy accepts 2 parameters: async, domain. Required: domain. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for content_taxonomy: 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 Mcp Knowledge. Nothing to install.
content_taxonomy 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_taxonomy 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_taxonomy. 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_taxonomy is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Mcp Knowledge, and thousands of servers like it.
This server
Across the catalogue