AI Economy Intelligence — aggregates ArXiv research + GitHub trending + job pivots + AI model prices + AI tokens + AI regulatory news into a comprehensive AI industry intelligence report. Use this tool when: - An AI-focused research agent needs a complete picture of the AI ecosystem in one call -...
AI agents call run_bundle_ai_economy to retrieve information from Omni Service Node without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool aggregates and returns intelligence data from multiple sources (ArXiv, GitHub, job data, prices, tokens, news). It is purely a read/fetch operation with no side effects. Severity is medium because it is a pay-per-call endpoint on Base Mainnet via USDC (x402), meaning an AI agent could inadvertently trigger repeated financial micropayments by calling it, even though the tool itself only retrieves data.
From the tool's definition aggregates ArXiv research + GitHub trending + job pivots + AI model prices + AI tokens + AI regulatory news into a comprehensive AI industry intelligence report
Attacks that exploit this kind of access
AI Economy Intelligence — aggregates ArXiv research + GitHub trending + job pivots + AI model prices + AI tokens + AI regulatory news into a comprehensive AI industry intelligence report. Use this tool when: - An AI-focused research agent needs a complete picture of the AI ecosystem in one call - A VC agent wants to assess AI industry momentum across research, hiring, and markets - You need to track AI adoption signals across multiple dimensions simultaneously - A strategy agent is building an AI market thesis and needs comprehensive inputs Returns: latest_arxiv_breakthroughs, github_trending_ai_repos, top_ai_hiring_companies, model_price_changes, ai_token_performance, regulatory_updates, ai_economy_momentum_score. Example: runBundleAiEconomy({ focus:. It is categorised as a Read tool in the Omni Service Node MCP Server, which means it retrieves data without modifying state.
Register the Omni Service Node MCP server in PolicyLayer and add a rule for run_bundle_ai_economy: 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 Omni Service Node. Nothing to install.
run_bundle_ai_economy 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 run_bundle_ai_economy 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 run_bundle_ai_economy. 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.
run_bundle_ai_economy is provided by the Omni Service Node MCP server (luckkyyy23/omni-service-node). 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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