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Salesbot - B2B outreach LinkedIn MCP Server with CRM and email

list_crm_companies

Read-onlyIdempotent

Use for company accounts already in the CRM. For companies only imported from LinkedIn use list_companies. List companies (accounts) in the CRM with people_count and the furthest pipeline stage reached by anyone at the company. Companies are created automatically from lead company names (matched ignoring case, diacritics and legal suffixes) and from LinkedIn company imports. Optional query searches name, industry and location. Returns crm_company_id for get_crm_company, update_crm_company and merge_crm_companies.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum rows (default 50, max 200).
queryNoOptional text search across company name, industry and location.
stageNoOptional: only companies where someone is in this pipeline stage (e.g. replied, demo).
offsetNoPagination offset (default 0).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real value beyond them: the return contents (people_count, furthest pipeline stage), and the auto-creation + case/diacritic/legal-suffix-insensitive matching behavior. It omits pagination/limit behavior, keeping it short of a 5.

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?

Front-loaded routing guidance followed by return-content and matching details; each sentence carries information. It runs slightly long with the auto-creation aside, but nothing is filler.

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?

Despite having no output schema, the description explains what is returned and how the id feeds downstream tools, and it covers creation semantics and the sibling boundary. Nothing an agent needs to select and invoke it correctly is missing.

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 schema already documents all four parameters including the query fields and stage meaning. The description only restates the query scope, adding no syntax or format detail beyond the schema. Baseline 3 applies.

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?

States a specific verb and resource ('List companies (accounts) in the CRM') and explicitly distinguishes itself from the sibling list_companies. An agent can tell the two apart without opening either schema.

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

Usage Guidelines5/5

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

Front-loads the when-to-use condition ('company accounts already in the CRM') and names the alternative for the excluded case ('For companies only imported from LinkedIn use list_companies'). It also points to the downstream tools (get/update/merge_crm_company) that consume the returned id.

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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