Medium Risk

bulk_modify

Add or remove labels on all messages matching a query. Same fast search-then-batch pattern as bulk_trash, but for arbitrary label ops. Use this for archive (remove_labels=['INBOX']), bulk star/unstar, mark-read across a label, moving messages between labels, etc. Use dry_run to see the count first.

Accepts freeform code/query input (query); Accepts file system path (folder); Bulk/mass operation — affects multiple targets

Part of the Mailbox MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

mailbox-mcp Write

AI agents use bulk_modify to create or modify resources in Mailbox. 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 bulk_modify repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Mailbox.

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

mailbox.yaml
tools:
  bulk_modify:
    rules:
      - action: allow
        rate_limit:
          max: 30
          window: 60

See the full Mailbox policy for all 49 tools.

Tool Name bulk_modify
Category Write
MCP Server Mailbox MCP Server
Risk Level Medium

View all 49 tools →

Agents calling write-class tools like bulk_modify have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.

What does the bulk_modify tool do? +

Add or remove labels on all messages matching a query. Same fast search-then-batch pattern as bulk_trash, but for arbitrary label ops. Use this for archive (remove_labels=['INBOX']), bulk star/unstar, mark-read across a label, moving messages between labels, etc. Use dry_run to see the count first.. It is categorised as a Write tool in the Mailbox MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on bulk_modify? +

Add a rule in your Intercept YAML policy under the tools section for bulk_modify. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Mailbox MCP server.

What risk level is bulk_modify? +

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

Can I rate-limit bulk_modify? +

Yes. Add a rate_limit block to the bulk_modify rule in your Intercept 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 bulk_modify completely? +

Set action: deny in the Intercept policy for bulk_modify. 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 bulk_modify? +

bulk_modify is provided by the Mailbox MCP server (mailbox-mcp). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Let agents act without letting them run wild.

Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.

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