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read_email

Retrieve complete email content including body, headers, and attachments by specifying an email ID. This tool enables AI agents to access and process email data for verification and information extraction tasks.

Instructions

Read the full content of a specific email including body, headers, and attachments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
email_idYesThe email ID to read

Implementation Reference

  • The 'read_email' tool is registered and implemented directly in mcp-server/src/index.ts. It takes an email_id as input and fetches email data via a blipFetch request.
    server.tool(
      "read_email",
      "Read the full content of a specific email including body, headers, and attachments.",
      {
        email_id: z.string().describe("The email ID to read"),
      },
      async ({ email_id }) => {
        const result = await blipFetch(`/v1/emails/${email_id}`);
        return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
      }
    );
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Discloses what data is accessed (body, headers, attachments) but omits critical behavioral details: whether this marks emails as read, idempotency, permissions required, or attachment return formats (base64 vs URLs).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with zero redundancy. Every phrase ('full content', 'body, headers, and attachments') earns its place by clarifying scope.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so description appropriately compensates by enumerating returned components (body, headers, attachments). Deducted one point for lack of format/structure details given these complex return types (attachments especially).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (email_id fully described). Description mentions 'specific email' which loosely corresponds to the parameter, but adds no additional semantic detail (ID format, examples, constraints). Baseline 3 appropriate for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Provides specific verb ('Read'), resource ('email'), and scope ('full content including body, headers, and attachments'). Effectively distinguishes from siblings like 'list_inboxes' (metadata), 'wait_for_email' (async arrival), and 'extract_codes' (filtered content).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage context by specifying 'full content' retrieval, suggesting when to use this over 'extract_codes' or 'get_inbox'. However, lacks explicit guidance on when to prefer alternatives (e.g., 'use extract_codes if you only need verification codes').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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