AI Agent Starter Pack — calls compliance + market sentiment + trading signals + macro data + news in a single bundled request. Ideal for agents that need a broad market context snapshot. Use this tool when: - An agent is initialising and needs a full market brief before starting work - You want 5...
AI agents invoke run_bundle_starter to trigger actions in Omni Service Node. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
Although this tool primarily retrieves data (Read-category endpoints like market sentiment, macro data, news), it is an Execute tool because: (1) it bundles and orchestrates multiple API calls in a single action, (2) it explicitly triggers external operations across compliance and trading signal systems, and (3) the sibling context ('56 pay-per-call MCP endpoints' with 'USDC on Base Mainnet via x402') indicates…
From the tool's definition 'run_bundle_starter' executes a bundled request that calls multiple endpoints (compliance, market sentiment, trading signals, macro data, news) in a single operation.
Attacks that exploit this kind of access
AI Agent Starter Pack — calls compliance + market sentiment + trading signals + macro data + news in a single bundled request. Ideal for agents that need a broad market context snapshot. Use this tool when: - An agent is initialising and needs a full market brief before starting work - You want 5 tools. It is categorised as a Execute tool in the Omni Service Node MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Omni Service Node MCP server in PolicyLayer and add a rule for run_bundle_starter: 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_starter 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 run_bundle_starter 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_starter. 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_starter 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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