Skip to main content
Glama

Server Details

Network hardware BOMs, built inside your AI assistant

If you are the author of this connector, you can claim ownership by verifying the domain or GitHub account it belongs to. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
Status
Healthy
Uptime
68.6% over 22 days
OAuth
Works in Glama
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

A4.2/5.0

Scored across 3 tools

Disambiguation5/5

Each tool targets a distinct stage of a linear workflow: listing use cases, starting a session, and submitting step input. There is no overlap in purpose, and the descriptions clearly delineate the sequence.

Naming Consistency5/5

All three tools follow the exact same bom_<verb>_<noun> snake_case pattern. The naming is fully predictable and self-describing.

Tool Count4/5

Three tools is on the thin side, but the session-based conversational design justifies a minimal surface where bom_submit_input drives most of the work. It is well-scoped rather than padded.

Completeness3/5

The build lifecycle (list → start → iterate) is covered, but the surface implies saved BOMs exist yet offers no tool to retrieve, view, export, or delete a completed/saved BOM. These are notable gaps that could cause dead ends after a session completes.

Available Tools

3 tools
bom_list_use_casesList BOM Use CasesA
Read-onlyIdempotent
Inspect

List available use-case profiles for BOM building. Each use case represents a deployment scenario (e.g. campus access, data center top-of-rack). Start here to understand what kinds of BOMs you can build.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered structurally. The description adds value beyond that by explaining the semantic content of each returned item ('represents a deployment scenario'), which helps an agent decide whether the output is what it needs. No return format or pagination detail, but the list is presumably small and static.

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 short sentences, zero waste, front-loaded with the action and followed by the definition and the routing cue. Every sentence earns its place.

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?

With no parameters, no output schema and complete annotation coverage, the description supplies what an agent needs: what the tool returns and why to call it first. It could go slightly further by naming the sibling tools it precedes, but it is functionally complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to disambiguate, and it correctly avoids inventing filtering options.

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?

The description states a specific verb and resource ('List available use-case profiles for BOM building') and clarifies what a use case is by giving concrete examples (campus access, data center top-of-rack). It does not explicitly name the sibling tools it complements, but the list/session/submit distinction is implicit in 'Start here'.

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?

'Start here to understand what kinds of BOMs you can build' gives clear entry-point context, implying this should be called before bom_start_session or bom_submit_input. No explicit when-not or alternative routing, but the sequencing guidance is unambiguous.

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

bom_start_sessionStart BOM SessionAInspect

Begin a new BOM building session for a specific use case. Returns a session_id and the first step's options. The session_id must be passed to bom_submit_input for subsequent steps. Use bom_list_use_cases first to see available use case IDs.

ParametersJSON Schema
NameRequiredDescriptionDefault
use_case_idYesUse case identifier (e.g. "campus-access", "dc-tor", "dc-core", "wan-edge", "smb", "campus-dist", "load-balancer", "ai-fabric")

TDQS

A4.3/5.0
Behavior4/5

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

Annotations declare non-read-only, non-idempotent, non-destructive, closed-world, but don't explain the session model. The description fills that gap by disclosing that a session_id and the first step's options are returned, and that the id must be threaded into bom_submit_input. It omits auth/permission requirements, 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each load-bearing: what it does, what it returns, and the prerequisite tool. No repetition of the name or title.

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?

No output schema exists, yet the description compensates by naming the return payload (session_id plus first-step options). Combined with the 100%-covered single-param schema and clear sibling routing, an agent has everything needed to call this correctly.

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% and the single parameter is documented with concrete example IDs, so the schema already carries the semantics. The description adds no format or constraint detail beyond it; 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+resource+scope: 'Begin a new BOM building session for a specific use case.' This is clearly distinguishable from bom_list_use_cases (enumeration) and bom_submit_input (advancing a session).

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?

Explicitly instructs 'Use bom_list_use_cases first to see available use case IDs' and names bom_submit_input as the follow-on tool, establishing the workflow ordering. It doesn't state a when-not-to-use condition, but for a step-0 tool this covers the practical selection need.

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

bom_submit_inputSubmit BOM InputAInspect

Submit user input for the current step of a BOM session. The message can be free text or one of the decision_chips returned by the previous step. Returns the updated BOM state, next step options, and decision chips. Continue calling this tool with the session_id until the session reaches the COMPLETE step. Going back or changing an earlier answer removes the affected lines from this in-progress draft; they can be chosen again, and no saved BOM is deleted.

ParametersJSON Schema
NameRequiredDescriptionDefault
messageYesUser input — either free text or one of the decision_chips from the previous response
session_idYesSession ID from bom_start_session

TDQS

A4.3/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false, idempotentHint=false, destructiveHint=false, which the description does not contradict; it adds genuine context by clarifying that going back or changing an answer prunes lines from the in-progress draft only, and no saved BOM is deleted. It also names the return payload. Missing details on error/retry behavior keep it below 5.

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?

Four tight sentences, front-loaded with the action, then the loop contract, then the state-mutation caveat. No repetition or filler; every clause earns its place.

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?

With no output schema, the description compensates by naming the return values (updated BOM state, next step options, decision chips) and by explaining the termination condition and session continuity. An agent has everything needed to drive the session correctly.

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% and the schema already explains both message (free text or decision_chip) and session_id (from bom_start_session). The description restates the message semantics without adding format, length, or escaping guidance, so 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 ('Submit') plus resource ('user input for the current step of a BOM session'), and the sibling set (bom_start_session, bom_list_use_cases) makes clear this is the continuation/driving loop rather than session creation. Distinguishable without opening a schema.

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?

Gives explicit operating context: call repeatedly with the same session_id until the session reaches the COMPLETE step, and that the message may be free text or a decision_chip from the previous step. Lacks explicit exclusions relative to siblings, but the loop condition is actionable.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 3 tool updates
    • First observedbom_list_use_cases
    • First observedbom_start_session
    • First observedbom_submit_input

Publisher details

Operator
Kirin Solutions LLC · Publisher source
Vendor relationship
First-party
Trust center
Not available
Restrictions
Up to 15 BOMs generated for free per month, then paid plan · Publisher source

Related MCP Connectors

Related MCP Servers

  • A
    license
    A
    quality
    C
    maintenance
    Enables AI assistants to search millions of electronic components and ICs, retrieve specifications, compare alternates, and submit turnkey BOM procurement requests.
    4
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI-assisted management of multi-vendor network devices (Cisco, Juniper, Nokia, Arista, Linux) through natural language, supporting health checks, configuration changes, routing analysis, and automation workflows.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Provides AI assistants with direct access to multi-vendor network devices for tasks like configuration management, health checks, and topology discovery through 35 specialized tools. It enables natural language control over platforms including Cisco, Juniper, and Nokia using SSH, NETCONF, and SNMP protocols.
    12
    MIT
Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources