Skip to main content
Glama
Sign In

Emailchaser

by com.emailchaser
OverviewDiscussionsAdmin

List AI reply drafts

list_reply_drafts
Read-only

Lists AI-suggested reply drafts awaiting review, newest first, 20 per page. Each draft answers the inbound reply referenced by inReplyToEmailId. Nothing here has been sent: a draft stays a draft until it is sent. A draft's subject and body can be edited before it goes out.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

NameRequiredDescriptionDefault
pageNoPage number, starting at 1
limitNoPage size (default 20, max 200)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already establish that this is a read-only, non-destructive, closed-world operation. The description adds meaningful lifecycle context: drafts are unsent, remain editable, are returned newest first, and answer the inbound reply referenced by inReplyToEmailId. It does not cover permissions or response metadata, but it adds useful behavioral clarity beyond the annotations.

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

Conciseness4/5

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

The description is short and front-loaded, with the core listing behavior stated first and lifecycle context following. The sentence 'a draft stays a draft until it is sent' is slightly redundant with the preceding clause, but the overall structure is efficient.

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 read-only listing tool with two optional pagination parameters and no output schema, the description covers ordering, page size, draft lifecycle, and the relationship to inbound replies. It does not describe the response shape or pagination metadata, but it provides enough context to call the tool correctly.

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%, so the page and limit parameters are already documented in the schema. The description restates the default page size of 20 but adds no new syntax or constraint details beyond what the schema provides.

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 states a specific verb and resource: it lists AI-suggested reply drafts awaiting review. It adds ordering and pagination details, making the purpose concrete. However, it does not explicitly distinguish this from nearby tools such as list_replies, so sibling differentiation is only implicit.

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?

Usage is implied by 'awaiting review' and by the note that drafts can be edited before sending, which hints at update_reply_draft and send_reply_draft. But there is no explicit when-to-use guidance or named alternative for listing sent replies versus pending drafts.

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

All Emailchaser toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources