manage_org_member
Manages organization membership: action 'invite' adds a member by email with a role, 'set_role' changes a member's role, 'remove' removes the member. Roles for organizations: 'admin' (manage members and displays), 'manager' (manage displays and content), 'viewer' (read-only); families accept 'chi...
This record as markdown: /tools/de-agentview-agentview-mcp/manage-org-member.md
What manage_org_member does on agentView
AI agents use manage_org_member 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 |
|---|---|---|---|
role | string | — | Role for 'invite' and 'set_role': 'admin', 'manager', 'viewer' (families: 'child'). |
email | string | — | Email address to invite (action 'invite'). |
action | string | Yes | Membership operation. |
org_id | string | Yes | Organization ID. |
access_token | string | — | Optional bearer token; prefer session_request_id. |
target_user_id | string | — | Member user ID (actions 'set_role' and 'remove'). |
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 manage_org_member is rated Medium
An AI agent can call manage_org_member 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) · Admin/system-level operation
Attacks that exploit this kind of access
The rule that runs manage_org_member 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 manage_org_member, this is the rule to start with:
manage_org_member 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 manage_org_member call is checked against it from then on.
Questions about manage_org_member
Manages organization membership: action 'invite' adds a member by email with a role, 'set_role' changes a member's role, 'remove' removes the member. Roles for organizations: 'admin' (manage members and displays), 'manager' (manage displays and content), 'viewer' (read-only); families accept 'child'. Requires admin 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.
manage_org_member accepts 7 parameters: role, email, action, org_id, access_token, target_user_id, session_request_id. Required: action, org_id. 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 manage_org_member: 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.
manage_org_member 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 manage_org_member 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 manage_org_member. 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.
manage_org_member 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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