HeyLead

Overview Schema Source Related Servers Discussions Admin

inbox

Read-only

Manage LinkedIn inbox conversations: list chats, read threads, reply, and review or approve comment drafts before sending.

Instructions

Browse and read LinkedIn inbox messages directly.

Read any conversation in your LinkedIn inbox, not just campaign contacts.

Args:
    action: What to do:
        "list" — List recent conversations with last message preview
        "read" — Read full conversation thread
        "reply" — Send a message to any inbox conversation
        "comment_drafts" — Replies drafted for comments on your own posts,
            waiting for your approval. Nothing is sent until you approve.
        "approve_draft" — Send one drafted reply (chat_id = draft id).
            Pass text= to send an edited version instead.
        "discard_draft" — Throw a draft away without sending (chat_id = draft id)
    chat_id: Chat ID to read (from list output). For 'read' and 'reply' actions.
        For 'approve_draft' and 'discard_draft', the draft id.
    name: Contact name to search for (partial match). For 'read' and 'reply' actions.
    limit: Max conversations (list) or messages (read) to show. Default 30.
    text: Message text to send. Required for 'reply' action.

Input Schema

TableJSON Schema

Name	Required	Default
`name`	No
`text`	No
`limit`	No
`action`	No	list
`chat_id`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.10.375Sep 18, 2026

TDQS

B3.4/5.0

Behavior1/5

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

The description includes actions that send messages (reply, approve_draft) and discard drafts, which are clearly mutating operations. Yet the annotations declare readOnlyHint=true, which contradicts the described behavior. This is a serious inconsistency that undermines trust in the tool's safety profile.

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 organized with a clear action list and parameter explanations. It is somewhat long but every sentence adds value, and the main purpose is front-loaded. The structure makes it easy to scan and reference.

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?

The description covers all actions and parameters, including special cases like drafts. It also clarifies the tool's scope. Given the presence of an output schema, it does not need to describe return values. It is sufficiently complete for an agent to invoke correctly, aside from the annotation contradiction.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by explaining each parameter's role and constraints. For example, chat_id is defined as 'Chat ID to read (from list output). For 'read' and 'reply' actions. For 'approve_draft' and 'discard_draft', the draft id.' This adds crucial meaning beyond the bare schema fields.

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 tool browses and reads LinkedIn inbox messages, and enumerates specific actions (list, read, reply, comment_drafts, etc.). It distinguishes from the general inbox concept but does not explicitly compare to sibling tools like backfill_inbox, so it is not a full 5.

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?

It provides context that it works on any conversation, not just campaign contacts, which hints at scope. However, it does not explicitly state when to prefer this tool over alternatives or when not to use it. The action-specific notes (e.g., drafts require approval) are useful but do not constitute tool selection guidance.

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