Add a participant to a WhatsApp group
AI agents use add_group_participant to create or update resources in Mcp Ap2 — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Ap2 environment.
This tool modifies group state by adding a participant to an existing WhatsApp group. It is reversible (the participant can be removed later) and has side effects limited to group composition. It does not delete, destroy, execute arbitrary code, or move money.
From the tool's definition Tool description states 'Add a participant to a WhatsApp group' — this creates/modifies a group's membership by adding a user, which is a reversible write operation.
Documented attack patterns abuse exactly the kind of access add_group_participant gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Ap2, and nothing reaches the server without passing your rules. This is the rule we recommend for add_group_participant:
{
"version": "1",
"default": "deny",
"tools": {
"add_group_participant": {
"limits": [
{
"counter": "add_group_participant_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} add_group_participant 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.
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Add a participant to a WhatsApp group. It is categorised as a Write tool in the Mcp Ap2 MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Mcp Ap2 MCP server in PolicyLayer and add a rule for add_group_participant: 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 Mcp Ap2. Nothing to install.
add_group_participant 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 add_group_participant 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 add_group_participant. 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.
add_group_participant is provided by the Mcp Ap2 MCP server (@codespar/mcp-ap2). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mcp Ap2, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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