descope-mcp-server
OfficialServer Quality Checklist
Latest release: v1.0.0
- Disambiguation2/5
The tools 'create-user' and 'invite-user' have significant overlap in purpose, as both involve creating new users, which could cause confusion for an agent. The other tools target distinct resources (audits vs. users), but the core user creation ambiguity is problematic.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with hyphens (e.g., create-user, search-audits), making them predictable and readable. There are no deviations in naming style across the set.
Tool Count3/5With only 4 tools, the set feels thin for a user management and audit domain, potentially lacking operations like update-user, delete-user, or get-user. However, it covers basic creation and search functions, placing it in a borderline range.
Completeness2/5For a user management server, there are significant gaps: no update, delete, or get operations for users, and audit functionality is limited to search only. This incomplete surface will likely cause agent failures in handling full user lifecycles.
Average 2.9/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- 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
- Behavior2/5
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 states the tool creates a user but doesn't mention required permissions, whether the operation is idempotent, what happens on duplicate loginIds, or what the response contains. For a mutation tool with 15 parameters, this leaves critical behavioral traits undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero wasted verbiage. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (15 parameters, nested objects, no output schema, and no annotations), the description is inadequate. It doesn't explain what happens after creation, error conditions, or system behavior. For a user creation tool in an authentication system, this leaves too many contextual gaps for reliable agent operation.
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 100%, so the schema already documents all 15 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema. This meets the baseline of 3 when the schema does the heavy lifting, but the description doesn't compensate with any extra context about parameter interactions or requirements.
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 action ('Create a new user') and the resource ('in Descope project'), providing a specific verb+resource combination. However, it doesn't differentiate from the sibling 'invite-user' tool, which likely serves a related purpose. The purpose is clear but lacks sibling differentiation.
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 like 'invite-user'. There's no mention of prerequisites, context, or exclusions. The agent must infer usage from the tool name alone, which is insufficient for informed selection.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. While it indicates this is a creation/invitation operation, it doesn't mention what permissions are required, whether this sends actual invitations versus just creating user records, what happens if the user already exists, or what the response contains. For a mutation tool with 20 parameters and no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized and front-loaded with the essential information, making it easy for an agent to quickly understand what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 20 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what happens after invocation (does it return the created user object? an invitation link?), what errors might occur, or any behavioral nuances. The agent would struggle to use this tool effectively without trial and error.
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?
The schema description coverage is 100%, meaning all 20 parameters are documented in the input schema itself. The description adds no additional parameter information beyond what's already in the schema descriptions, so it meets the baseline expectation but doesn't provide extra value regarding parameter usage or relationships.
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 action ('Create and invite') and target resource ('a new user to the Descope project'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from the sibling 'create-user' tool, which appears to serve a similar purpose but without the invitation aspect.
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 like 'create-user' or other sibling tools. There's no mention of prerequisites, when this tool is appropriate versus other user management approaches, or any exclusions or limitations.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It doesn't indicate whether this is a read-only operation, what permissions might be required, whether results are paginated, or what format the audit logs will be returned in. The description merely restates the tool name without adding meaningful behavioral context beyond what's implied by 'Search'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single four-word phrase that efficiently communicates the core function. There's no wasted language or unnecessary elaboration. The description is appropriately sized for a search tool with well-documented parameters in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 9 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what audit logs contain, how results are structured, whether there are rate limits, or what authentication might be required. The agent would need to rely heavily on trial-and-error or external knowledge to use this tool effectively, especially given the lack of output schema.
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?
The input schema has 100% description coverage, with each parameter clearly documented in the schema itself. The tool description adds no additional parameter information beyond what's already in the schema descriptions. According to the scoring guidelines, when schema_description_coverage is high (>80%), the baseline score is 3 even with no parameter information in the description.
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 verb ('Search') and resource ('Descope project audit logs'), making the tool's purpose immediately understandable. However, it doesn't differentiate this audit log search tool from the sibling 'search-users' tool, which searches a different resource type. The description is specific about what's being searched but doesn't clarify the distinction from similar search operations.
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 about when to use this tool versus alternatives. There's no mention of prerequisites, appropriate contexts, or comparison with sibling tools like 'search-users'. The agent must infer usage from the tool name and parameters alone, which is insufficient for optimal tool selection.
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?
With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose whether this is a read-only operation, potential rate limits, authentication requirements, or what the return format looks like (e.g., paginated results). This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero waste, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain behavioral aspects like pagination handling, result format, or error conditions, leaving the agent with insufficient context to use the tool effectively beyond basic parameter input.
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?
The input schema has 100% description coverage, so the schema fully documents all 12 parameters. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline of 3 where schema does the heavy lifting without extra value from the description.
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 verb ('Search for') and resource ('users in Descope project'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search-audits' beyond the resource name, missing explicit distinction in scope or function.
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?
No guidance is provided on when to use this tool versus alternatives like 'create-user' or 'invite-user', nor does it mention prerequisites or contextual constraints. The description only states what it does, not when it's appropriate.
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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