read_email
Use this when the user wants the full content of an email that lives in the Mac's Apple Mail (message ID from list_emails/search_emails). For a Microsoft 365 message ID from m365_list_emails, use m365_read_email. Pass account= (and mailbox= if known, both from list_emails/search_emails) so the lo...
This record as markdown: /tools/com-local-mcp-local-mcp/read-email.md
What read_email does on Local
AI agents call read_email to retrieve information from Local without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
account | string | — | |
mailbox | string | — | |
message_id | string | Yes | |
include_body | boolean | — | |
max_body_chars | integer | — |
Parameters from the server's own tool schema.
Why read_email is rated Low
This tool retrieves email data with no side effects. It reads from Apple Mail using a message ID and account/mailbox parameters. The only potential concern is privacy (accessing email content), but the action itself is a Read operation that queries and returns data without modifying it.
From the tool's definition Tool name is 'read_email' and description states 'Use this when the user wants the full content of an email' — retrieves email content from Apple Mail. No modification, deletion, execution, or financial operations are performed.
Attacks that exploit this kind of access
The rule that runs read_email safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Local, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For read_email, this is the rule to start with:
read_email is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Local, apply this rule, and every read_email call is checked against it from then on.
Questions about read_email
Use this when the user wants the full content of an email that lives in the Mac's Apple Mail (message ID from list_emails/search_emails). For a Microsoft 365 message ID from m365_list_emails, use m365_read_email. Pass account= (and mailbox= if known, both from list_emails/search_emails) so the lookup targets one account instead of scanning all of them. Call sequentially, not in parallel — concurrent calls serialize behind Mail.app's JXA lock and later calls will time out. Performance: body fetch is the primary latency source (avg 20s on slow IMAP). Pass include_body=false to skip it and get metadata-only (fast). Pass max_body_chars=N to cap the body at N chars after HTML stripping (default 30000; 0=unlimited). Response includes body_fetch_ms when fetch took >2s, body_omitted=true when skipped, body_truncated_at=N when cut. It is categorised as a Read tool in the Local MCP Server, which means it retrieves data without modifying state.
read_email accepts 5 parameters: account, mailbox, message_id, include_body, max_body_chars. Required: message_id. The full parameter table on this page comes from the server's own tool schema.
Register the Local MCP server in PolicyLayer and add a rule for read_email: 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.
read_email is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the read_email 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 read_email. 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.
read_email 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.
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