Skip to main content
Glama
ZilongXue

ClaudePost

by ZilongXue

get-email-content

Retrieve the full content of an email by its unique ID using ClaudePost's email management interface, enabling efficient access to specific email details directly.

Instructions

Get the full content of a specific email by its ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
email_idYesThe ID of the email to retrieve

Implementation Reference

  • Main handler logic for the 'get-email-content' tool within the handle_call_tool function. Extracts email_id, fetches the email content asynchronously, formats it, and returns as text content.
    elif name == "get-email-content":
        email_id = arguments.get("email_id")
        if not email_id:
            return [types.TextContent(
                type="text",
                text="Email ID is required."
            )]
        
        try:
            async with asyncio.timeout(SEARCH_TIMEOUT):
                email_content = await get_email_content_async(mail, email_id)
                
            result_text = (
                f"From: {email_content['from']}\n"
                f"To: {email_content['to']}\n"
                f"Date: {email_content['date']}\n"
                f"Subject: {email_content['subject']}\n"
                f"\nContent:\n{email_content['content']}"
            )
            
            return [types.TextContent(
                type="text",
                text=result_text
            )]
            
        except asyncio.TimeoutError:
            return [types.TextContent(
                type="text",
                text="Operation timed out while fetching email content."
            )]
  • JSON Schema defining the input parameters for the 'get-email-content' tool, requiring 'email_id' as a string.
    inputSchema={
        "type": "object",
        "properties": {
            "email_id": {
                "type": "string",
                "description": "The ID of the email to retrieve",
            },
        },
        "required": ["email_id"],
    },
  • Registration of the 'get-email-content' tool in the list_tools handler using types.Tool, including name, description, and input schema.
    types.Tool(
        name="get-email-content",
        description="Get the full content of a specific email by its ID",
        inputSchema={
            "type": "object",
            "properties": {
                "email_id": {
                    "type": "string",
                    "description": "The ID of the email to retrieve",
                },
            },
            "required": ["email_id"],
        },
    ),
  • Helper function to asynchronously fetch the full email content (RFC822) using IMAP for a given email_id and format it.
    async def get_email_content_async(mail: imaplib.IMAP4_SSL, email_id: str) -> dict:
        """Asynchronously get full content of a specific email."""
        loop = asyncio.get_event_loop()
        try:
            _, msg_data = await loop.run_in_executor(None, lambda: mail.fetch(email_id, '(RFC822)'))
            return format_email_content(msg_data)
        except Exception as e:
            raise Exception(f"Error fetching email content: {str(e)}")
  • Helper function to parse email bytes into a dictionary with headers (from, to, date, subject) and body content, handling multipart and plain emails.
    def format_email_content(msg_data: tuple) -> dict:
        """Format an email message into a dict with full content."""
        email_body = email.message_from_bytes(msg_data[0][1])
        
        # Extract body content
        body = ""
        if email_body.is_multipart():
            # Handle multipart messages
            for part in email_body.walk():
                if part.get_content_type() == "text/plain":
                    body = part.get_payload(decode=True).decode()
                    break
                elif part.get_content_type() == "text/html":
                    # If no plain text found, use HTML content
                    if not body:
                        body = part.get_payload(decode=True).decode()
        else:
            # Handle non-multipart messages
            body = email_body.get_payload(decode=True).decode()
        
        return {
            "from": email_body.get("From", "Unknown"),
            "to": email_body.get("To", "Unknown"),
            "date": email_body.get("Date", "Unknown"),
            "subject": email_body.get("Subject", "No Subject"),
            "content": body
        }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves email content but doesn't mention any behavioral traits such as permission requirements, rate limits, error handling, or what 'full content' includes (e.g., attachments, headers). This leaves significant gaps for an agent to understand how to use it effectively.

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?

The description is a single, clear sentence that directly states the tool's function without any unnecessary words. It's appropriately sized and front-loaded, making it efficient for an agent to parse.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'full content' entails (e.g., text body, HTML, metadata) or provide any context about the return format, which is crucial for a retrieval tool. This leaves the agent with insufficient information to handle the tool's output effectively.

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?

The schema description coverage is 100%, with the parameter 'email_id' fully documented in the schema. The description adds no additional meaning beyond what the schema provides (e.g., format examples or constraints), so it meets the baseline score of 3.

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?

The description clearly states the action ('Get') and resource ('full content of a specific email'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search-emails' which might also retrieve email content, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'search-emails' or 'count-daily-emails'. It mentions retrieving by ID but doesn't specify scenarios where this is preferred over other retrieval methods.

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

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ZilongXue/claude-post'

If you have feedback or need assistance with the MCP directory API, please join our Discord server