Pure, bounded analysis of an explicit bill-of-materials graph: validates structure, finds missing...
Pure, bounded analysis of an explicit bill-of-materials graph: validates structure, finds missing references, duplicate IDs, duplicate edges, and cycles (whole graph, even parts unreachable from the root), and - when the graph is completely clean - exactly explodes root quantity through every assembly level with exact-decimal arithmetic, aggregating shared components reached via different branches. No network access and no manufacturing/supplier certification: this checks the data you supply, not the real world. Price: 0.05 USDC per completed bounded job on Base.
| Name | Required | Description | Default |
|---|---|---|---|
| root | Yes | ID of the part to explode from. Must match one of parts[].id. | |
| parts | Yes | ||
| quantity | Yes | Positive exact decimal, <=12 integer digits, <=6 fraction digits. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses important behavioral traits: whole-graph analysis even for parts unreachable from the root, explosion only when the graph is completely clean, exact-decimal arithmetic, aggregation of shared components across branches, bounded execution, and a per-job price. This is exceptionally transparent about how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but efficient, with the core scope and behavior front-loaded in the first sentence. Every clause adds useful information, including the boundary conditions and price. The first sentence is long and could be split for readability, but there is no meaningful waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex analysis tool with no output schema, the description provides strong context: validation checks, edge cases, arithmetic precision, cost, and the boundary between data validation and real-world certification. The main gap is that it does not describe the exact return format or response shape, which is more significant given there is no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67%: root and quantity have their own descriptions, but the parts parameter is only described structurally and lacks a top-level description. The tool description adds conceptual meaning—parts form the BOM graph and quantity is exploded through assembly levels—but it does not fully compensate for the undocumented parts parameter or explain parameter relationships beyond what the schema already states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource (an explicit bill-of-materials graph) and a precise set of behaviors: validating structure, finding missing references, duplicate IDs, duplicate edges, and cycles, and exploding root quantity through assembly levels. This is far more specific than the tool name and leaves little ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly frames when the tool applies—analysis of user-supplied BOM data—and when it does not: 'No network access and no manufacturing/supplier certification' and 'checks the data you supply, not the real world.' It does not name a sibling alternative, but no siblings are listed, so the guidance is appropriately explicit for the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
bill_of_materials_integrityClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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With only one tool, there is no possibility of ambiguous tool selection or overlapping responsibilities. The single tool's purpose is clearly and comprehensively stated, so an agent cannot confuse it with any other.
The tool name is a clear, descriptive snake_case noun phrase that matches the server's purpose. There are no mixed naming conventions to penalize, though the lack of a verb_noun pattern means it does not perfectly align with the strongest convention.
A single tool is borderline for an MCP server, but here it bundles a logically coherent set of BOM validation and explosion operations into one bounded analysis service. It is thin but not absurdly under-scoped for its stated purpose.
The tool covers the core BOM integrity domain: structural validation, reference checks, duplicate detection, cycle detection, and quantity explosion. It is intentionally bounded to supplied data, and no obvious critical operation is missing for that stated scope.