# 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.

Agent View of the PolicyLayer registry record for `content_taxonomy`. HTML page: https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/content-taxonomy

## Facts

- Tool: `content_taxonomy`
- Server: Mcp Knowledge (`https://mcp.gapup.io`) — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge.md
- Homepage: https://github.com/getgapup/gapup-mcp
- Risk category: Read (Low risk)
- Registry record: grade F, identity unverified
- Server auth posture: open
- Server rate-limited: no
- Parameters: 2 (1 required)
- Recommended policy verdict: Allowed

## Parameters

| Parameter | Type | Required | Description |
| --- | --- | --- | --- |
| `async` | boolean | no | 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.

## Example call (MCP tools/call, JSON-RPC 2.0)

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "content_taxonomy",
    "arguments": {
      "domain": "<domain>"
    }
  }
}
```

## 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 own 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 signals: Bulk/mass operation — affects multiple targets

## Use case

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.

## Recommended policy (PolicyLayer)

Verdict: **Allowed**. Enforced by the PolicyLayer MCP gateway (https://policylayer.com/mcp-gateway) before a call reaches Mcp Knowledge:

```json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "content_taxonomy": {}
  }
}
```

## Other tools on Mcp Knowledge (270)

- `adversarial_input_stress_tester` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/adversarial-input-stress-tester.md
- `competitor_pricing_scrape` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/competitor-pricing-scrape.md
- `dora_operational_resilience_stress_tes` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/dora-operational-resilience-stress-tes.md
- `financial_model_3statement` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/financial-model-3statement.md
- `gl_reconciler` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/gl-reconciler.md
- `lgpd_data_subject_rights_automator` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/lgpd-data-subject-rights-automator.md
- `monte_carlo_portfolio` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/monte-carlo-portfolio.md
- `workflow_orchestrator` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/workflow-orchestrator.md
- `ma_arbitrage_hunter` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ma-arbitrage-hunter.md
- `repo_rate_arbitrage_scanner` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/repo-rate-arbitrage-scanner.md
- `tax_optimization` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/tax-optimization.md
- `treasury_optimizer` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/treasury-optimizer.md
- `usdc_x402_payments_intel` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/usdc-x402-payments-intel.md
- `working_capital_fx_hedge_optimizer` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/working-capital-fx-hedge-optimizer.md
- `pricing_in_deal` — Other — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/pricing-in-deal.md
- `term_sheet_negotiation` — Other — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/term-sheet-negotiation.md
- `abm_architect` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/abm-architect.md
- `abm_lookalike_account_finder` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/abm-lookalike-account-finder.md
- `account_expansion_mapper` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/account-expansion-mapper.md
- `affiliate_fraud_clickstream_detector` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/affiliate-fraud-clickstream-detector.md
- `africa_trade_barrier_breaker` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-barrier-breaker.md
- `africa_trade_finance_esg_rater` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-finance-esg-rater.md
- `africa_trade_preference_arbitrage` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-preference-arbitrage.md
- `africa_trade_preference_optimizer` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-preference-optimizer.md
- `agoa_eba_intelligence` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/agoa-eba-intelligence.md
- `ai_act_sandbox_regulatory_sandbox` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-act-sandbox-regulatory-sandbox.md
- `ai_act_training_data_audit` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-act-training-data-audit.md
- `ai_governance_full_report_async` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-full-report-async.md
- `ai_governance_full_report_result` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-full-report-result.md
- `ai_governance_pilot` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-pilot.md
- …and 240 more: https://policylayer.com/tools/io-github-getgapup-mcp-knowledge.md

## For agents

This record is a snapshot. Live verdicts and the full registry:

- Check every server in your MCP config at once: `npx -y policylayer stack`
- Vet a server before you add it: install the mcp-precheck skill — `npx skills add https://policylayer.com` (skill text: https://policylayer.com/skill.md)
- Query the registry over MCP: endpoint `https://api.policylayer.com/mcp` — tools `check_mcp_server`, `check_mcp_stack`, `check_tool`, `search_registry`, `get_change_events`

---

Source: the PolicyLayer MCP registry — one continuously verified record per MCP server. Full record: https://policylayer.com/registry?q=io-github-getgapup-mcp-knowledge · API: https://policylayer.com/registry/api · Policy library: https://policylayer.com/policies/io-github-getgapup-mcp-knowledge