submit_feedback
Sends the user's feedback, feature request or bug report about agentView itself (not display content) for later review. Confirm the exact wording with the user before sending; optional sentiment. There is no automatic reply. Requires content scope.
This record as markdown: /tools/de-agentview-agentview-mcp/submit-feedback.md
What submit_feedback does on agentView
AI agents use submit_feedback to create or update resources in agentView, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your agentView environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
message | string | Yes | The user's verbatim feedback text (max 2000 characters). Pass what the user actually said; do not paraphrase or add your own commentary. |
sentiment | string | — | Optional overall sentiment of the feedback. Set only when the user's tone is clear; omit if unsure. |
access_token | string | — | Optional bearer token; prefer session_request_id. |
session_request_id | string | — | Session handle from create_auth_session; pass it on every authenticated call. |
Parameters from the server's own tool schema.
Why submit_feedback is rated Medium
An AI agent can call submit_feedback faster than any human can review: one bad instruction and it creates or modifies resources in agentView by the hundred, each call as confident as the last.
Risk signalsHandles credentials or secrets (access_token)
Attacks that exploit this kind of access
The rule that runs submit_feedback safely
PolicyLayer is an MCP gateway: it sits between your AI agents and agentView, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For submit_feedback, this is the rule to start with:
submit_feedback 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 agentView, apply this rule, and every submit_feedback call is checked against it from then on.
Questions about submit_feedback
Sends the user's feedback, feature request or bug report about agentView itself (not display content) for later review. Confirm the exact wording with the user before sending; optional sentiment. There is no automatic reply. Requires content scope. It is categorised as a Write tool in the agentView MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
submit_feedback accepts 4 parameters: message, sentiment, access_token, session_request_id. Required: message. The full parameter table on this page comes from the server's own tool schema.
Register the agentView MCP server in PolicyLayer and add a rule for submit_feedback: 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 agentView. Nothing to install.
submit_feedback 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 submit_feedback 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 submit_feedback. 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.
submit_feedback is provided by the agentView MCP server (https://agentview.de/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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