NetBox MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The three tools have clearly distinct purposes: netbox_get_changelogs retrieves audit logs of changes, netbox_get_object_by_id fetches a single object by ID, and netbox_get_objects lists objects by type with filtering. There is no overlap in functionality, making it easy for an agent to select the right tool for each task.
Naming Consistency5/5All tool names follow a consistent snake_case pattern with the prefix 'netbox_' and a descriptive verb_noun structure: get_changelogs, get_object_by_id, get_objects. This uniformity makes the tool set predictable and easy to understand at a glance.
Tool Count3/5With only three tools, the server feels thin for the broad domain of NetBox, which includes many object types across DCIM, IPAM, circuits, virtualization, tenancy, VPN, and wireless. While the tools cover basic read operations, the count is borderline low given the extensive scope implied by the object_type list.
Completeness2/5The tool set is severely incomplete for a NetBox server, as it only provides read operations (get) with no support for create, update, or delete. This leaves significant gaps in CRUD/lifecycle coverage, which will likely cause agent failures when trying to perform common administrative tasks like adding devices or modifying IP addresses.
Average 3.2/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states this is a read operation ('Get detailed information'), which implies it's non-destructive, but doesn't disclose other behavioral traits like authentication requirements, rate limits, error handling, or what happens if the ID doesn't exist. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise: a clear purpose statement followed by Args and Returns sections. Every sentence adds value, with no redundant information. However, the 'Returns' section is vague ('Complete object details'), which slightly reduces efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and parameters but lacks details on usage guidelines, behavioral transparency, and output specifics. Without annotations or an output schema, more context on return values and error cases would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds basic semantics: 'object_type' is a 'String representing the NetBox object type (e.g. "devices", "ip-addresses")' and 'object_id' is 'The numeric ID of the object.' This clarifies what each parameter represents, but doesn't provide examples beyond a few object types or explain format constraints (e.g., case sensitivity, allowed values). It partially compensates for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed information about a specific NetBox object by its ID.' It specifies the verb ('Get'), resource ('NetBox object'), and key constraint ('by its ID'). However, it doesn't explicitly differentiate from sibling tools like 'netbox_get_objects' (which likely lists multiple objects) or 'netbox_get_changelogs' (which focuses on change history).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'netbox_get_objects' (for listing objects) or 'netbox_get_changelogs' (for audit logs), nor does it specify prerequisites such as needing to know the object ID beforehand. Usage is implied but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions that filters are based on NetBox API filtering options and lists object types, but it doesn't disclose behavioral traits like whether this is a read-only operation, potential rate limits, authentication needs, error handling, or pagination. The description is functional but lacks critical operational context for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, but it includes a lengthy, bulleted list of object_type values that could be considered excessive. While this list adds value, it makes the description less concise. The structure is clear with sections for args and valid values, but it could be more streamlined for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (2 parameters, no annotations, no output schema, nested objects in filters), the description is partially complete. It covers parameter semantics well but lacks behavioral transparency and output details. Without annotations or an output schema, it should ideally explain more about the tool's behavior and return values to be fully adequate for agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining both parameters. It defines object_type as a string representing NetBox object types and provides an extensive list of valid values. It describes filters as a dict based on NetBox API filtering options, adding meaningful context beyond the bare schema. However, it doesn't detail the structure or examples of filter dicts.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get objects from NetBox based on their type and filters.' It specifies the verb ('Get') and resource ('objects from NetBox'), distinguishing it from siblings like netbox_get_object_by_id (which fetches a single object by ID) and netbox_get_changelogs (which retrieves change logs). However, it doesn't explicitly differentiate from netbox_get_changelogs beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by listing valid object_type values and referencing the NetBox API for filtering, but it doesn't explicitly state when to use this tool versus alternatives. For example, it doesn't clarify that netbox_get_object_by_id is for retrieving a single object by ID, while this tool is for filtered queries. The guidance is present but not explicit about alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's function and output format, including details like the structure of changelog entries and filtering options. However, it omits critical behavioral traits such as rate limits, authentication requirements, pagination handling, or error conditions, which are important for safe and effective use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns, Filtering options, Example, Each changelog entry) and uses bullet points for readability. It is appropriately sized for the tool's complexity, though some sentences could be more concise (e.g., the changelog entry list is verbose). Overall, it is efficient and front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (1 parameter with nested objects, no output schema, no annotations), the description is largely complete. It explains the purpose, parameters, return values, and includes examples. However, it lacks information on behavioral aspects like error handling or performance, which would enhance completeness for a tool with no structured annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage and only defines a generic 'filters' object. The description compensates fully by detailing all filtering options (e.g., user_id, action, time_before) with explanations and examples, adding significant meaning beyond the schema. This comprehensive parameter documentation is essential given the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get object change records (changelogs) from NetBox based on filters.' It specifies the verb ('Get'), resource ('object change records'), and scope ('from NetBox based on filters'), which is clear and specific. However, it does not explicitly differentiate from sibling tools like netbox_get_objects, which likely retrieves objects rather than their change logs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as the sibling tools netbox_get_object_by_id or netbox_get_objects. It includes examples of filter usage but does not mention prerequisites, exclusions, or contextual cues for selection. This lack of comparative guidance limits its utility in tool selection.
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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