This record as markdown: /tools/io-github-aibtcdev-mcp-server/inference-check-provider.md
What inference_check_provider does on Aibtc
AI agents invoke inference_check_provider to trigger actions in Aibtc. 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.
Why inference_check_provider is rated High
The description 'Re-run the marketplace' implies executing or triggering some marketplace process. This falls under Execute as it appears to trigger an external operation. However, the description is vague and uninformative, which lowers confidence.
From the tool's definition 'Re-run the marketplace' suggests triggering an external operation or process execution
Attacks that exploit this kind of access
The rule that runs inference_check_provider safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Aibtc, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For inference_check_provider, this is the rule to start with:
inference_check_provider stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Aibtc, apply this rule, and every inference_check_provider call is checked against it from then on.
Questions about inference_check_provider
Re-run the marketplace. It is categorised as a Execute tool in the Aibtc MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Aibtc MCP server in PolicyLayer and add a rule for inference_check_provider: 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 Aibtc. Nothing to install.
inference_check_provider 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 inference_check_provider 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 inference_check_provider. 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.
inference_check_provider is provided by the Aibtc MCP server (aibtcdev/aibtc-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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