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bcharleson

Instantly MCP Server

get_account

Read-only

Retrieve account details, warmup status, and campaign eligibility by email to check connection status, daily limits, and sending configuration.

Instructions

Get account details, warmup status, and campaign eligibility by email.

Returns comprehensive account information including:

  • Connection status and provider info

  • Warmup configuration and progress

  • Daily limits and sending gaps

  • Tracking domain settings

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The core handler function that executes the get_account tool logic: fetches account details via API using the provided email.
    async def get_account(params: GetAccountInput) -> str:
        """
        Get account details, warmup status, and campaign eligibility by email.
        
        Returns comprehensive account information including:
        - Connection status and provider info
        - Warmup configuration and progress
        - Daily limits and sending gaps
        - Tracking domain settings
        """
        client = get_client()
        email_encoded = quote(params.email, safe="")
        result = await client.get(f"/accounts/{email_encoded}")
        return json.dumps(result, indent=2)
  • Pydantic input schema defining the required 'email' parameter for the get_account tool.
    class GetAccountInput(BaseModel):
        """Input for getting account details."""
        
        model_config = ConfigDict(str_strip_whitespace=True, extra="ignore")
        
        email: str = Field(..., description="Account email address")
  • TOOL_ANNOTATIONS dictionary entry registering the get_account tool with readOnlyHint metadata.
    "list_accounts": {"readOnlyHint": True},
    "get_account": {"readOnlyHint": True},
  • ACCOUNT_TOOLS list that includes get_account for dynamic loading and registration in the MCP server.
    ACCOUNT_TOOLS = [
        list_accounts,
        get_account,
        create_account,
        update_account,
        manage_account_state,
        delete_account,
    ]
Behavior4/5

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds valuable behavioral context beyond annotations by detailing the comprehensive information returned (e.g., connection status, warmup progress, daily limits), which helps the agent understand the tool's output scope and utility without contradicting annotations.

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 front-loaded with the core purpose in the first sentence, followed by a bulleted list that efficiently details return values without redundancy. Every sentence earns its place by adding clarity, and the structure is well-organized for quick comprehension.

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

Completeness5/5

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

Given the tool's complexity (single parameter, read-only operation), the description is complete: it states the purpose, details the return values (compensating for no output schema in the context signals), and aligns with annotations. The presence of an output schema (per context signals) further reduces the burden on the description, making this adequately comprehensive.

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 0%, but the description compensates by specifying the parameter's purpose ('by email') and the input schema clearly defines a required 'email' parameter of type string. The description adds minimal semantics beyond the schema, but the schema itself is straightforward, making a baseline score of 3 appropriate.

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?

The description clearly states the tool's purpose with specific verbs ('Get account details, warmup status, and campaign eligibility by email') and distinguishes it from siblings like 'list_accounts' (which likely lists multiple accounts) and 'update_account' (which modifies accounts). It specifies the resource (account) and key attributes retrieved.

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

Usage Guidelines4/5

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

The description implies usage context by specifying retrieval 'by email' and listing the types of information returned, which helps differentiate it from siblings like 'list_accounts' (no email parameter) or 'get_campaign' (different resource). However, it does not explicitly state when not to use it or name alternatives.

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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