Compare and rank product mentions across multiple podcast shows using cached extractions — no re-run. Collapses a 3-call manual join into 1 tool call. Performs entity resolution to identify the same product mentioned across shows. Returns ranked cross-show product list with per-show context, aver...
Handles credentials or secrets (api_key)
Part of the Podcast Commerce Intelligence MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents invoke compare_products_across_shows to trigger processes or run actions in Podcast Commerce Intelligence. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
compare_products_across_shows can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
tools:
compare_products_across_shows:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: trueSee the full Podcast Commerce Intelligence policy for all 5 tools.
Agents calling execute-class tools like compare_products_across_shows have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
compare_products_across_shows is one of the high-risk operations in Podcast Commerce Intelligence. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.
Compare and rank product mentions across multiple podcast shows using cached extractions — no re-run. Collapses a 3-call manual join into 1 tool call. Performs entity resolution to identify the same product mentioned across shows. Returns ranked cross-show product list with per-show context, average confidence, and recommendation consensus. Use for multi-show affiliate research, best-of page generation, and cross-show brand ranking. Supports physical_goods, saas, supplement, and all other categories. Requires prior extract_podcast_products calls for each show_id.. It is categorised as a Execute tool in the Podcast Commerce Intelligence MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Add a rule in your Intercept YAML policy under the tools section for compare_products_across_shows. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Podcast Commerce Intelligence MCP server.
compare_products_across_shows is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the compare_products_across_shows rule in your Intercept 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 Intercept policy for compare_products_across_shows. 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.
compare_products_across_shows is provided by the Podcast Commerce Intelligence MCP server (sincetoday/podcast-commerce-mcp). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept