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himalaya-mcp

himalaya-mcp

by Data-Wise

read_email_raw

Retrieve the full, unedited MIME source of an email, including all headers, for debugging, forensics, or exporting to .eml format.

Instructions

Read the raw MIME source of an email. Returns the full, unedited message including all headers. Useful for debugging, email forensics, and exporting to .eml format.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "read_email_raw"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesEmail message ID
folderNoFolder name (default: INBOX)
accountNoAccount name (uses default if omitted)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.2.2
    • addedInput schema / properties / id / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "maximum": 9007199254740991,
      +    "minimum": 0,
      +    "type": "integer"
      +  }
      +]
    • removedInput schema / properties / id / type
      Removed value: -"string"
  2. Addedv2.0.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden. It usefully discloses what the payload contains (unedited message, all headers), but says nothing about side effects — notably whether fetching raw MIME marks the message as read — nor about size limits or attachment/binary encoding handling.

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?

Two sentences, purpose front-loaded, then concrete use cases. No filler and nothing the agent must read past to find the core statement.

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?

For a simple three-parameter read tool with no output schema, the description adequately communicates the return content and the common use cases. The remaining gap is behavioral rather than structural: no statement on read/unread side effects or message size limits.

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 description coverage is 100% and all three parameters (id, folder, account) are documented inline, including the INBOX default. The description adds no parameter-level meaning beyond what the schema already provides, so baseline 3 applies.

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

Purpose4/5

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

States a specific verb and resource ('Read the raw MIME source of an email') and pins down the return shape ('full, unedited message including all headers'). The 'raw MIME' framing functionally separates it from siblings like read_email and read_email_html, though those siblings are never named explicitly.

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?

Offers use cases ('debugging, email forensics, exporting to .eml') which implies when to reach for it, but gives no explicit contrast such as 'use read_email instead for the parsed body' or 'use read_email_html for rendered content'. The agent must infer the alternative from the sibling list.

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