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LinkedIn MCP Server (Salesbot)

by cz.salesbot

get_chat_messages

Read-onlyIdempotent

Read the messages of a single LinkedIn conversation in real time (newest last). Use the chat_id from list_inbox_chats. is_sender=true marks messages sent by the account owner (you). Use this to understand context before composing a reply with reply_to_chat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax messages (1-50, default 15)
cursorNoPagination cursor. Optional.
chat_idYesChat ID from list_inbox_chats
profile_idNoUUID of the user_profile. Optional — defaults to active profile.

TDQS

A4.4/5.0
Behavior5/5

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

Adds behavioral details beyond annotations: 'real time', 'newest last' ordering, and the `is_sender` flag in response. Consistent with readOnlyHint and idempotentHint 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?

Three concise sentences front-loading purpose, then usage context. No wasted words; every sentence adds value.

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?

No output schema; description mentions response field `is_sender` but not full return structure. Adequate given simplicity and annotations, but could note pagination.

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 coverage is 100% with parameter descriptions. Description does not add significant meaning beyond schema, but provides context for chat_id source.

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?

Description clearly states 'Read the messages of a single LinkedIn conversation in real time', specifying the verb and resource. It distinguishes from siblings by referencing chat_id from list_inbox_chats and connecting to reply_to_chat.

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?

Provides explicit context: use to understand conversation before composing a reply, and chat_id source. Does not list exclusions or alternatives, but guidance is clear.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap among search tools (search_job_postings, search_google_xray, search_linkedin_people, search_web) and messaging tools (send_connection_request, send_linkedin_message, reply_to_chat). However, detailed descriptions clarify the differences.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (e.g., add_contacts_to_campaign, list_campaigns). No mixing of conventions.

Tool Count3/5

48 tools is high but justifiable given the broad domain (LinkedIn outreach, CRM, campaigns, job postings, etc.). However, some tools could be consolidated (e.g., multiple search tools).

Completeness5/5

The tool set covers the entire workflow: searching, connecting, messaging, campaign management, CRM operations (fields, stages, tasks, notes), job postings, and posting. No obvious gaps.

Resources