Medium Risk

teams_send_message

Send a message to a Microsoft Teams chat via Graph API. Requires connect_m365_account. chat_id must come from teams_list_chats. First call returns preview; set confirm=true to send.

Part of the Local server.

teams_send_message can modify Local data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use teams_send_message to create or modify resources in Local. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call teams_send_message repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Local.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "teams_send_message": {
      "limits": [
        {
          "counter": "teams_send_message_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access teams_send_message gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so teams_send_message only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the teams_send_message tool do? +

Send a message to a Microsoft Teams chat via Graph API. Requires connect_m365_account. chat_id must come from teams_list_chats. First call returns preview; set confirm=true to send.. It is categorised as a Write tool in the Local MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on teams_send_message? +

Register the Local MCP server in PolicyLayer and add a rule for teams_send_message: 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 Local. Nothing to install.

What risk level is teams_send_message? +

teams_send_message is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit teams_send_message? +

Yes. Add a rate_limit block to the teams_send_message 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.

How do I block teams_send_message completely? +

Set action: deny in the PolicyLayer policy for teams_send_message. 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.

What MCP server provides teams_send_message? +

teams_send_message is provided by the Local MCP server (local-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Local tool call.

Deterministic rules across all 108 Local tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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