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SupplyGraph.AI

Enterprise Supply Graph Visualization Agent

sg_visualization

Generates global multi-tier supply-chain graphs providing full visibility into enterprise and product dependencies.

Pricing: {"unit": "credits", "per_run": 264590}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pidYesInternal company ID for the target enterprise, obtained from the search_company_candidates MCP tool (e.g. a77828f060c866441f2403384b271e63 for Tesla, Inc.).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.4/5.0
Behavior2/5

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

With openWorldHint=true, the tool may have external side effects, but the description doesn't disclose what those are. It only mentions pricing (which is useful) but lacks details on persistence, external calls, or irreversible actions. No contradiction, but minimal behavioral disclosure.

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 very concise—one sentence plus pricing. It front-loads the core purpose and avoids fluff. However, given the complexity of the tool and its sibling context, a slightly longer description with usage guidance would be more helpful without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema exists and the parameter is fully documented, but the description lacks usage guidance and behavioral context (e.g., when to use this over other supply-chain tools, any prerequisites beyond pid). It's adequate for a simple read-like tool, but the openWorldHint suggests more context could be needed.

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?

The input schema fully describes the single pid parameter, including its source and an example. The tool description adds no extra meaning beyond what the schema already provides, so the baseline of 3 is appropriate given high schema coverage.

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?

The description clearly states the tool's function: generates global multi-tier supply-chain graphs with full dependency visibility. This is specific and distinguishes it from sibling tools like supply_chain_risk_prediction or sg_chokepoint, which focus on analysis or risk rather than visualization.

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?

The description implies usage by mentioning the pid input comes from search_company_candidates, but it doesn't explicitly state when to use this tool versus alternatives. There's no guidance on scenarios where visualization is preferred over reports or risk prediction, leaving the agent to infer based on tool names.

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

B3/5.0
Disambiguation3/5

Tools are generally distinct in purpose (search, due diligence, tariff, supply chain), but the two 'search_company_candidates' and 'search_region_candidates' are similar in name and both serve lookup functions, and multiple tools like 'corporate_exception_report' and 'due_diligence_report' overlap in producing comprehensive company reports. The separation is clear enough for an agent but could cause confusion between similar-sounding search tools.

Naming Consistency3/5

Names mix styles: descriptive multi-word names (due_diligence_report, supply_chain_risk_prediction) and abbreviated names (sg_chokepoint, sg_visualization). There is no consistent verb_noun pattern, and the 'sg_' prefix is inconsistently applied. However, most names are readable and roughly follow a noun-based pattern.

Tool Count5/5

With 9 tools, the server covers a broad but coherent domain: search/identity, due diligence, supply chain analysis, and tariff compliance. Each tool addresses a distinct high-level capability, and the count feels appropriate for the scope—not too thin or overly heavy.

Completeness4/5

The tool surface covers major workflows: company identification, due diligence reporting, supply chain risk/chokepoint analysis, tariff classification and calculation. Minor gaps exist (e.g., no explicit update/delete on data since it's a read-only data provider), but for its purpose as an analysis API, it is reasonably complete.

Resources