candidate.accept
Accept only a candidate backed by its own passed transaction receipt.
This record as markdown: /tools/visionmcp/candidate.accept.md
What candidate.accept does on Visionmcp
AI agents use candidate.accept to create or update resources in Visionmcp, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Visionmcp environment.
Why candidate.accept is rated Medium
Accepting a candidate modifies state by committing/approving a candidate record backed by a transaction receipt. This is a write/approval action — it creates or confirms a persistent state change.
From the tool's definition Accept only a candidate backed by its own passed transaction receipt
Attacks that exploit this kind of access
The rule that runs candidate.accept safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Visionmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For candidate.accept, this is the rule to start with:
candidate.accept stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Visionmcp, apply this rule, and every candidate.accept call is checked against it from then on.
Questions about candidate.accept
Accept only a candidate backed by its own passed transaction receipt. It is categorised as a Write tool in the Visionmcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Vision MCP server in PolicyLayer and add a rule for candidate.accept: 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 Visionmcp. Nothing to install.
candidate.accept is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the candidate.accept 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 candidate.accept. 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.
candidate.accept is provided by the Vision MCP server (joshuahickscorp/visionmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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