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pitchmuc

Knowledge Graph MCP Server

by pitchmuc

list_accounts

Read-only

Retrieve enterprise accounts from a CRM knowledge graph, with optional filters for industry, tier, region, and minimum health score.

Instructions

List enterprise accounts in the knowledge graph, optionally filtered.

Args: industry: Case-insensitive substring match on industry (optional). tier: Exact match on account tier, e.g. "Strategic", "Enterprise", "Mid-Market" (optional). region: Exact match on region code, e.g. "NA", "EMEA", "APAC" (optional). min_health_score: Only return accounts with healthScore >= this value (optional, defaults to 0 i.e. no filtering).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNo
regionNo
industryNo
min_health_scoreNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the useful behavioral detail that min_health_score defaults to 0, meaning no filtering by default, but says nothing about result size, ordering, or pagination behavior.

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 opening sentence is front-loaded and the Args block is scannable with one line per parameter. It is slightly verbose in repeating '(optional)' four times and could drop the redundant default restatement, but nothing is confusing.

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?

An output schema exists, so return values need no explanation, and all four parameters are fully documented. The remaining gap is operational: no mention of result limits or pagination for what is otherwise an unbounded list endpoint.

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 schema description coverage at 0% (properties carry only titles and defaults), the description carries the full burden and does so: it specifies match semantics per parameter (case-insensitive substring for industry, exact match for tier and region), gives concrete example values, and explains the default for min_health_score. This is meaning the schema does not provide.

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?

States a specific verb and resource: 'List enterprise accounts in the knowledge graph', plus the scoping modifier 'optionally filtered'. It does not, however, distinguish itself from the sibling search_accounts, so an agent must infer which listing tool applies.

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

Usage Guidelines2/5

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

The description never says when to use this tool instead of search_accounts, get_account, or run_sparql_query, nor does it state any prerequisites or exclusions. Usage is only implied by the word 'List' and the optional filters.

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