Jamf Docs MCP Server

Server Quality Checklist

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Latest release: v4.3.3
Disambiguation5/5
Each tool has a clearly distinct purpose: list products, search articles, retrieve a single article, retrieve a TOC, glossary lookup, and batch retrieval. There is no functional overlap that would confuse an agent.
Naming Consistency4/5
All tools share the 'jamf_docs_' prefix, and most follow a verb-first pattern (list_products, get_article, get_toc, batch_get_articles). The exception is 'glossary_lookup', which puts the noun before the verb, creating a slight inconsistency.
Tool Count5/5
Six tools is well-scoped for a documentation server, covering core browsing, searching, retrieval, and batch needs. Each tool earns its place without unnecessary bloat.
Completeness5/5
The surface covers the full documentation workflow: discovering products, exploring TOCs, searching with filters, retrieving individual articles, fetching multiple articles, and looking up glossary terms. No obvious gaps or dead ends.
Average 4.6/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 123 commits in the last 12 weeks
- Last stable release on August 12, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces this with 'This is a read-only operation'. It adds useful behavioral context beyond annotations by explaining the return JSON structure, including tokenInfo with a truncated flag, and the difference between markdown and json output formats.
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 well-structured with clear sections (Main purpose, Args, Returns, Examples, Note) and front-loads the core purpose. It is slightly verbose due to examples and return format details, but every part serves a purpose and no information is redundant.
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?
The description fully covers the tool's role and output. With an output schema present, it still explains both JSON and Markdown return formats, includes token truncation behavior, and gives concrete example queries. It also mentions docType filters, which connects to sibling search tools, making it contextually complete.
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 has 100% coverage for all three parameters with descriptions and defaults. The description restates the parameters but adds minimal new insight—mainly the implication that 'compact' mode yields a brief list. Since the schema already explains the parameters well, the description does not need to compensate significantly.
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 states 'List all available Jamf products, topics, and their documentation versions' with a specific verb and resource. It clearly differentiates from sibling tools like jamf_docs_search, which searches rather than lists. The scope is explicit, listing examples like Jamf Pro and Jamf School.
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?
Provides clear context and examples for when to use the tool: 'What Jamf products are available?' and 'What topics can I filter by?'. However, it does not explicitly mention alternatives or when not to use it, leaving room for a more direct comparison with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as read-only, idempotent, and non-destructive, but the description adds important behavioral context beyond that: it mentions 'Large articles are intelligently truncated with remaining sections listed,' lists possible errors (404, invalid URL, section not found), and clarifies that summaryOnly is a token-efficient preview. These details help the agent predict and handle edge cases without contradicting any annotations.
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 well-structured with clear sections (Args, Returns, Examples, Errors, Note) and is front-loaded with the main purpose. While it is lengthy, every section serves a purpose, and the JSON return example is useful given the tool's complexity. It is slightly redundant with the schema (e.g., listing default values), but that redundancy is acceptable for discoverability.
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?
Given the tool's complexity (10 parameters, output schema, sibling tools), the description is highly complete. It covers return formats, error handling, truncation behavior, and provides multiple usage examples. The existence of an output schema does not reduce the value of the description's own Returns section, which clarifies how each parameter affects the response.
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 schema descriptions cover 100% of parameters, so baseline is 3. The description adds examples and explains token efficiency, but its Args list omits mapId, contentId, and language, and incorrectly labels url as 'required' when the schema has no required fields. This misleading detail undermines the added value, making it a net-neutral contribution beyond the schema.
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 purpose: 'Retrieve the full content of a specific Jamf documentation article.' It uses a specific verb (retrieve) and resource (article), and distinguishes itself from siblings like search, list_products, and get_toc by focusing on fetching a known article's content.
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?
Provides clear context on when to use the tool: 'Works with any article from docs.jamf.com or learn.jamf.com.' Includes examples (e.g., full article, specific section, maxTokens) and a note about using the section parameter for long articles. However, it does not explicitly mention alternative tools like search or list_products, so it stops short of giving exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive, but the description adds substantial behavioral context: it explains the return structure (mapId, contentId, tokenInfo, pagination), how outputMode affects nesting, how structuredContent flattens the TOC with depth values, and how markdown vs JSON differ in exposing contentIds. It also discloses error types and the relationship with jamf_docs_get_article. This goes well beyond the annotations.
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?
Though long, the description is efficiently structured with clear sections (Args, Returns, Examples, Errors, Note). Every sentence adds functional value: parameter details, return format, usage examples, error handling, and cross-tool integration. The opening sentence front-loads the purpose, and the note clarifies edge cases without redundancy.
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?
Given the tool's complexity—7 parameters, multiple output formats, pagination, structuredContent behavior, and integration with jamf_docs_get_article—the description is remarkably complete. It covers all aspects an agent needs: what it does, when to use it, how parameters affect behavior, what the return looks like, errors, and examples. The presence of an output schema does not reduce the need for this contextual detail, and the description delivers it fully.
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?
Schema covers all 7 parameters with descriptions, enum values, and defaults, so baseline is 3. The description adds meaningful nuance beyond the schema, such as clarifying that outputMode='compact' gives 'flat list without nested children' (schema just says 'brief output') and explaining how responseFormat affects whether contentIds are visible. It also shows example parameter combinations. This extra context justifies a 4.
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 opens with a specific verb+resource: 'Get the table of contents for a Jamf product's documentation.' It clearly distinguishes this from sibling tools by focusing on navigation structure and topic discovery rather than search or article retrieval. The purpose is unambiguous and immediately actionable.
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?
The description explicitly states when to use the tool: 'Use this to discover what topics are available before searching or retrieving specific articles.' It also notes that large TOCs are paginated, implying you should handle pagination. While it doesn't explicitly contrast with every sibling tool, the discovery-first guidance is clear and useful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, but the description adds critical behavioral context: fuzzy matching, the English-only limitation for glossary content despite the language parameter, and the effect on results. It also discloses error messages and output structure, going well beyond the annotation baseline.
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?
The description is well-organized into clear sections (main purpose, note, Args, Returns, Examples, Errors) and remains readable despite its length. Every sentence contributes meaningful information, and the core purpose is front-loaded with no redundant fluff.
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?
Given the tool's complexity and the presence of a full output schema, the description thoroughly covers selection criteria, invocation parameters, output formats, examples, and potential error messages. It fully equips an agent to select and invoke the tool correctly without needing to infer details.
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?
Schema descriptions cover all 6 parameters, but the description enriches them by explaining the English-only caveat for the language parameter, providing illustrative examples for term and product, and detailing the JSON return structure. This adds value beyond the schema's baseline.
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 purpose with a specific verb and resource: 'Look up a term in the Jamf official glossary and get its definition.' It distinguishes itself from sibling tools like jamf_docs_search and jamf_docs_get_article by focusing exclusively on glossary terms and mentioning fuzzy matching.
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?
The description provides clear context for when to use this tool: to look up glossary terms. It includes examples of natural language queries and offers parameters for filtering by product. However, it does not explicitly state when not to use it or directly name alternatives, falling short of the full 'when/when-not' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, the description discloses result ranking by relevance, error messages ('No results found', 'Invalid product ID'), the mapId/contentId behavior with fallback to URL, pagination limits, and output modes. This goes well beyond what annotations provide and fully informs the agent of behavioral nuances.
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?
Although long, the description is well-structured into clear sections (intro, Args, Returns, Examples, Errors, Note). Every section serves a purpose and is front-loaded with the core purpose. There is no redundant or filler content given the tool's complexity.
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?
The description is highly complete for a search tool with 11 parameters and an output schema. It covers all parameter semantics, return formats, error scenarios, pagination, and cross-references to sibling tools. The presence of an output schema does not diminish the need for the detailed examples and behavioral notes, which are provided.
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 schema already has 100% coverage with descriptions for all 11 parameters. The description adds value by providing concrete query examples, recommended filter combinations, and explaining the mapId/contentId usage for results, which enriches the semantic understanding beyond merely restating schema constraints.
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 verb 'Search' and the resource 'Jamf documentation' with explicit scope across all products. It distinguishes itself from siblings by noting that results carry mapId/contentId to pass to jamf_docs_get_article, and references jamf_docs_list_products for filter options.
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?
The description provides clear context with example queries and recommended filters, and explicitly mentions alternatives like jamf_docs_get_article for direct article retrieval and jamf_docs_list_products for product IDs. However, it does not explicitly state when NOT to use this tool, though the examples imply typical usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: parallel execution with concurrency control, independent success/failure per article, partial failure reporting without failing the batch, and token budget distribution. No contradiction with annotations.
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?
The description is well-structured with Args, Returns, Examples, and Note sections. Every sentence adds useful information: constraints, defaults, behavioral notes, and examples. Despite its length, it is appropriately sized for a tool with six parameters and complex batch behavior, and it is front-loaded with the primary purpose.
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?
Given the tool's complexity (batch retrieval, concurrency, token budget, partial failures), the description covers all essential aspects: input constraints, parameter defaults, return format details, example usage, and fallback behavior. The presence of an output schema reduces the need to enumerate return fields, but the description still summarizes the return structure adequately.
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?
Every parameter in the schema has a description, and the tool description elaborates further with semantics such as 'Distributed evenly' for maxTokens, 'Use compact for brief output', and constraints like 'must be from docs.jamf.com or learn.jamf.com' for URLs. The description adds meaning beyond the schema's property descriptions.
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 retrieves multiple Jamf documentation articles in a single request, using a specific verb and resource. It explicitly mentions fetching up to 10 articles in parallel, which distinguishes it from the sibling tool jamf_docs_get_article that likely handles single articles.
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?
The description provides clear use cases: 'useful for comparing articles, gathering information from multiple pages, or bulk research.' It does not explicitly mention when not to use it or name alternative tools, but the context is sufficient for an agent to decide. A slightly lower score is given for missing explicit exclusions or alternatives.
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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