Intune Assignment Checker MCP

by ugurkocde

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Server Quality Checklist

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Latest release: v0.4.0
Disambiguation4/5
The tools are mostly distinct: connection checking, policy search, all-device listing, all-user listing, unassigned listing, and assignment lookup are separable operations. However, list_all_device_assignments, list_all_user_assignments, and list_unassigned_policies all return similar record shapes (policyId, pageSummary, coverage, cursor), which could cause an agent to conflate which list answers a given question.
Naming Consistency4/5
Seven of the expected tools use a consistent verb_noun pattern (get_connection_status, search_policies, list_all_device_assignments, list_all_user_assignments, list_unassigned_policies, get_policy_assignments). The naming is coherent and predictable, with only minor asymmetry around 'list_*' versus 'get_*' for read operations.
Tool Count5/5
Six tools is a well-scoped surface for an Intune assignment checker. Each tool fills a distinct role in the query workflow: authentication check, policy discovery, assignment targeting, and detailed assignment retrieval. The count is within the ideal 3-15 range and nothing feels redundant or missing at a coarse level.
Completeness3/5
The server covers the core assignment-checking workflow well: search, list by target, list unassigned, and get detailed assignments for one policy. However, there are notable gaps in the lifecycle—there is no way to see assignments for a specific discovered group beyond the single-policy lookup, no bulk get across multiple policies, and no overview/hierarchy tool that aggregates coverage. The domain is inherently about analysis, so create/update/delete don't apply, but the query surface has some dead ends (e.g., get_policy_assignments requires already knowing exact policyId and category from another tool).
Average 4.3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 commits in the last 12 weeks
- Last stable release on August 21, 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, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds valuable behavioral context: it discloses pagination scope ('resultCount, pageSummary, and graphUsage describe only the current tool call; follow nextCursor for complete coverage'), the opaque nature of the cursor, and conditional fields ('application intent when available'). These details go beyond annotations and help the agent understand the paginated, per-call nature of results.
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 three sentences with no filler. The primary purpose is stated first, followed by a focused usage tip, then a concise explanation of pagination behavior. Every sentence carries meaning, and the structure is logical.
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?
The tool has 4 parameters (none required) and an output schema, so per the rubric we don't demand return-field explanations. The description covers the core function, filters (category), and pagination (cursor), which are the most critical for correct invocation. It omits explicit guidance on 'limit' and 'platform', which could be inferred but are not documented. Given the pagination behavior is clearly stated, the description feels fairly complete for an agent to use successfully, though a brief note on limit would round it out.
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 0%, so the description bears the burden of parameter explanation. It does clarify two of the four parameters: 'category' (via 'set category to application') and 'cursor' (via 'opaque continuation cursor' and 'follow nextCursor'). However, 'limit' and 'platform' are not explained at all—no mention of pagination size or filtering by OS. Thus, only partial compensation for the low 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 opens with a specific verb and resource: 'Lists policies and applications that directly target All Devices.' It clearly differentiates from siblings like list_all_user_assignments (targets users) and list_unassigned_policies, and even narrows scope to 'directly target' to exclude inherited assignments. This leaves no 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides one direct usage tip: 'For questions about apps assigned to All Devices, set category to application.' However, it does not explicitly state when to use this tool over the siblings (e.g., 'use this for All Devices, not for user assignments') or mention exclusions. The implicit scope is clear from the name, but explicit routing to alternatives is absent, so it falls at implied usage rather than explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive behavior, lowering the bar. The description adds the constraint about not accepting Graph URLs/paths, which is extra behavioral context, but does not cover error handling or side effects beyond that.
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 two sentences with no unnecessary words. It front-loads the primary action (Returns) and scope (one supported policy), and the second sentence adds a clear constraint. Perfectly sized for the information provided.
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?
Given that the tool has an output schema, the description need not explain return values. It adequately covers the core purpose and a key input constraint. However, it does not mention prerequisites like authentication or typical error conditions, though these may be implicit in the tool context. Overall, sufficient for a simple read-only operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% for all parameters. The description only hints at a policy but does not explain policyId, category, limit, or cursor. It fails to map the 'one supported policy' concept to the policyId parameter or clarify the category enum's role, leaving the agent to guess parameter meanings from names alone.
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 (Returns) and resource (policy assignments) and scope (one supported policy), clearly distinguishing it from sibling tools like list_all_device_assignments or list_all_user_assignments. The added note 'It never accepts a Graph URL or path' further clarifies the input expectation.
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?
Implies usage for a single policy via 'for one supported policy' and clarifies input format with the URL/path prohibition, but does not explicitly compare to alternatives or state when to use them. The sibling names suggest the context, but the description itself could be more explicit about when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already cover read-only, idempotent, non-destructive behavior. The description adds meaningful context beyond that: it explicitly states that no token is returned or logged, which is important security-related behavior an agent should know.
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 a single, compact sentence that front-loads the core action and includes the most valuable security constraint without any filler. Every word 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?
For a zero-parameter, read-only, idempotent tool with a rich annotation set and an output schema, the description is complete. It covers what the tool does and the critical privacy behavior, leaving no operational ambiguity.
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 has zero parameters, so the baseline is 4. The description does not need to add parameter semantics, and it appropriately focuses on the operation's purpose and behavior.
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 uses a specific verb ('Checks') and identifies the exact resource and scope: 'local delegated Microsoft authentication'. It clearly distinguishes this from the sibling policy/assignment tools, which are unrelated in function.
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 intended use is implied: check authentication status before other operations. However, there is no explicit statement of when to use this tool versus alternatives, and no mention of exclusions or preconditions.
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 and idempotent, but the description adds meaningful behavioral context: results include 'an opaque continuation cursor' (pagination mechanism), 'graphUsage describes only the current tool call', and 'resultCount is the number of records on this page.' This clarifies pagination semantics and avoids misinterpretation of counts. It also discloses the specific field set returned. 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 three sentences long, each earning its place: the first defines the tool's scope, the second gives a specific parameter instruction, and the third describes output contents and pagination semantics. The main purpose is front-loaded, and there is no redundant or filler content. It is efficiently structured and easy to scan.
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?
The description is sufficient for a read-only list tool with an output schema that already defines the return structure. It covers pagination (cursor, per-page count) and key output fields. Minor gaps remain: it does not explain the 'platform' parameter or explicitly state how to request the next page (though the cursor implies it), and the meaning of 'supported' is not elaborated. Overall, the description is highly complete but slightly missing on parameter guidance.
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?
With 0% schema description coverage, the description carries the full burden of parameter explanation. It partially compensates by explaining the 'category' parameter ('set category to application') and implying the cursor's purpose ('opaque continuation cursor'), but it leaves 'limit' and 'platform' completely unexplained. The agent can infer limit from context, but the description does not explicitly state its meaning or range, so the parameter semantics are only partially addressed.
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 a specific verb ('Lists') and a precise resource: 'supported Intune policies and applications whose assignment collection is empty.' This clearly distinguishes the tool from siblings by focusing on unassigned items, and the additional instruction 'For unassigned apps, set category to application' reinforces the special case. It is unambiguous and differentiates the tool's purpose without needing to open the 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?
The description indicates when to use the tool: when you need policies/applications with empty assignment collections. It also provides a conditional guideline ('For unassigned apps, set category to application'), which helps the agent select the right category value. However, it does not explicitly name alternative tools like search_policies or list_all_device_assignments, nor does it state when NOT to use this tool, leaving some exclusion guidance implicit.
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?
Given readOnlyHint, idempotentHint and destructiveHint are already declared, the description adds meaningful behavioral context: pagination semantics, opaque continuation cursor, and the caveat that resultCount/pageSummary/graphUsage only cover the current call. This is valuable 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?
Three purposeful sentences with no filler. Scope is front-loaded and pagination details are succinctly placed at the end. Every sentence adds information.
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 provides the operation scope, category-specific use, and pagination behavior, plus the key output fields. With the output schema present and simple parameters, no critical aspects of correct usage are missing.
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 0%, so the description must compensate. It explains the category parameter's meaning and the continuation cursor's purpose, but does not describe the limit parameter or explicitly map the input cursor to the returned nextCursor. Partial compensation.
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 ('Lists') and a concrete resource ('policies and applications that directly target All Users'), plus a distinguishing scope. This clearly separates it from siblings like list_all_device_assignments and get_policy_assignments.
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 explicit guidance for one key decision: 'For questions about apps assigned to All Users, set category to application.' It does not explicitly name alternatives or exclusions, but the scope statement makes the intended use obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations by revealing that results come from 'internally generated Microsoft Graph /beta requests', that isAssigned values are 'Graph-reported hints', and that results can be RBAC-filtered. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, front-loads the core action, and every sentence delivers either a caveat (non-unique display names) or a routing hint (get_policy_assignments). It is slightly dense but remains readable and well-organized. It earns a high score, but not a 5 because it could be tighter by removing the redundant 'Searches supported' phrasing with the title.
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?
For a search-and-return tool, the description explains how to consume results and what caveats apply, and the output schema covers expected return values. It does not explicitly discuss pagination or cursor semantics, but those are parameters documented in the schema, so the description need not repeat them. The presence of an output schema further reduces the burden on the description.
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 description coverage is 0%, so the description carries the full burden. It explains the key output semantics (id and categoryId) and the critical non-uniqueness caveat. It does not explicitly name limit, cursor, or platform, but given the 0% schema coverage, the description compensates enough for an agent to understand the primary inputs and expected outputs.
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 a specific verb ('searches') and resource ('supported Intune policy and application categories') and differentiates it from siblings by being the path to get_policy_assignments via id/categoryId. It also calls out the non-uniqueness of display names, which clarifies a subtle edge case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states that returned id and categoryId should be passed as policyId and category to get_policy_assignments, and warns not to silently choose a single record when display names are not unique. It also clarifies that isAssigned values are only hints and get_policy_assignments reconciles them, giving clear, decision-relevant usage context.
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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