Fetch performance data for AI/ML sector crypto tokens: NEAR, FET (Fetch.ai), AGIX (SingularityNET), RNDR (Render), WLD (Worldcoin), TAO (Bittensor), and the full AI token sector. Use this tool when: - An agent is investing in the AI token narrative and needs sector performance - You want to compa...
AI agents call get_ai_tokens 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 is a read-only tool that retrieves and returns market data about cryptocurrency tokens. While the data could inform financial decisions, the tool itself performs no financial transactions, account modifications, or irreversible actions. It is pure information retrieval.
From the tool's definition Tool description states 'Fetch performance data' for crypto tokens, returning name, ticker, price_usd, market_cap, and percentage changes. No modification, deletion, or execution of external operations described.
Attacks that exploit this kind of access
Fetch performance data for AI/ML sector crypto tokens: NEAR, FET (Fetch.ai), AGIX (SingularityNET), RNDR (Render), WLD (Worldcoin), TAO (Bittensor), and the full AI token sector. Use this tool when: - An agent is investing in the AI token narrative and needs sector performance - You want to compare AI token performance vs BTC/ETH benchmark - A research agent is building a thesis on the AI crypto sector - An agent needs to identify which AI tokens are outperforming or underperforming Returns per token: name, ticker, price_usd, market_cap, 24h_change_pct, 7d_change_pct, 30d_change_pct, sector_rank, vs_btc_performance, narrative_tags. Example: getAiTokens({ limit: 10 }) → TAO +45% (7d), RNDR +28%, FET +18% — AI sector outperforming BTC this week. Cost: $0.005 USDC per call. 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 get_ai_tokens: 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.
get_ai_tokens 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 get_ai_tokens 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 get_ai_tokens. 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.
get_ai_tokens 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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