db-access-mcp

by Rheopyrin

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.4
Disambiguation5/5
Each tool has a clearly distinct purpose: connection management (find, list, test, tunnel operations), query execution (query, query_plan, query_to_file), and dialect support (dialect_list). No two tools have overlapping functionality.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with underscores (e.g., connection_list, query_plan, up_tunnel). The only exception is 'query' which is a simple verb, but it's a common and clear name for the primary operation.
Tool Count5/5
With 10 tools, the server is well-scoped. Each tool serves a specific need for database access and management, and the count is neither too small to be thin nor too large to be overwhelming.
Completeness5/5
The tool set covers all essential operations: listing/finding connections, testing, querying, explaining plans, exporting results, and managing tunnels. There are no obvious gaps for a database access server.
Average 4.5/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- Last stable release on July 13, 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?
Discloses that username/password filters are ignored and that metadata filters use AND logic. References return shape to connection_list. No annotations provided, so description compensates well.
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?
Two concise sentences, front-loaded with purpose and parameters. No fluff.
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?
Explains filtering behavior and return shape. Missing explicit behavior when no parameters provided, but inferred. Adequate for a non-complex tool.
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 coverage is 100%, but description adds value by clarifying ignored parameters and AND logic for metadata. Provides additional meaning 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?
Description clearly states the tool finds database connections by filtering on specific parameters. It distinguishes from connection_list by specifying filtering via parameters and referencing the same return shape.
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 implies use for filtering connections but lacks explicit guidance on when to choose this over connection_list or other tools. Sibling tool list provides context but no direct advice.
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 description implies a read-only operation by stating it lists dialects, but since no annotations are provided, the description carries the full burden. It does not explicitly state that the tool has no side effects, but the nature of the tool (listing) makes this clear. A score of 4 is appropriate as it is transparent enough for safe use.
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 sentence that efficiently conveys the tool's purpose and return value. It is concise, front-loaded, and contains no extraneous 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?
Given that there are no parameters, no output schema, and the tool is simple, the description fully explains what the tool does and what it returns (dialect name, default port, execution-plan format). It is complete for an agent to understand its use.
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?
There are no parameters, so the baseline score is 4. The description does not need to add parameter information, and it correctly reflects the tool's behavior without parameters.
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 action ('list'), the resource ('database dialects'), and the specific return fields (name, default port, execution-plan format). It effectively distinguishes this tool from the sibling tools, which deal with connections, queries, and tunnels.
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 explicitly states what the tool does but does not provide guidance on when to use it versus alternatives. The usage is implied (e.g., before configuring a connection), but no explicit when-not or exclusion criteria are given.
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?
No annotations are provided, so the description carries the full burden. It discloses truncation with a truncated flag, read-only enforcement, and driver-specific multi-statement behavior. It does not detail error handling or logging, but covers essential behavioral traits for a query tool.
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 concise with three sentences. The first sentence states the purpose and a helpful hint. Subsequent sentences efficiently detail truncation, read-only behavior, and multi-statement handling. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers key behaviors but lacks details on the return format (e.g., structure of results, handling of errors, or what happens with empty results). Given the absence of an output schema, more information about the response would improve completeness for a query tool.
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 coverage is 100%, so baseline is 3. The description adds value by explaining the connection parameter (use connection_list to discover keys), max_rows default from config, and multi-statement driver requirement for query. This goes beyond the schema descriptions, justifying a score of 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 clearly states the tool executes a SQL query on a configured connection, with a hint to discover connection keys. It distinguishes from sibling tools like query_plan and query_to_file by describing query execution behavior.
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 guidance on when to use (e.g., for SQL execution) and mentions prerequisites (use connection_list). It advises adding LIMIT for large tables and explains behavior for read-only connections and multi-statement scripts. However, it does not explicitly list alternatives or conditions to avoid using this tool.
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?
No annotations provided, so description carries full burden. It discloses non-execution, return format differences per dialect, and the redshift relative cost caveat. Lacks details on authorization or error responses.
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?
Two concise sentences. First sentence states core purpose, second sentence delivers essential usage guidelines. No wasted words.
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?
Covers purpose, non-execution, dialect differences, and redshift caveat. Missing details on error handling or output format details, but no output schema exists. Adequate for a tool with clear input schema.
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 coverage is 100%, baseline 3. The description adds value by reinforcing the query parameter is not executed and explaining dialect-specific behavior that is not in 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?
Clearly states the verb 'Get', resource 'execution plan', and distinguishes from running the query. The description explicitly says 'without running it', differentiating from the sibling tool 'query'.
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 specific guidance for different database dialects (postgres/mysql vs redshift) and warns about redshift cost numbers. Does not explicitly list when not to use, but the context is clear enough for most agents.
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?
No annotations provided, so description carries full burden. It discloses that credentials are never included, which is critical behavioral context. Lacks details on rate limits or ordering, but adequate for a listing tool.
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?
Two sentences, no waste. Front-loaded with purpose, followed by return details and usage guidance.
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 no output schema, description explains return shape sufficiently (fields and omission of credentials). Also advises on using the key with related tools. Complete for a listing tool.
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?
No parameters, schema coverage 100%. Baseline 4. Description adds meaning beyond schema by explaining what the tool returns and its usage context.
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 it lists configured database connections, specifies supported types (postgres, mysql, redshift), and enumerates returned fields (key, type, description, read_only, host/port/database, metadata). It distinguishes itself from sibling tools like connection_find and connection_test.
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?
It explicitly states when to use the tool ('List configured database connections') and how to use the output (key with query, query_plan, up_tunnel). Does not mention when not to use, but context from siblings implies alternatives.
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?
No annotations are provided, so the description fully carries the burden of behavioral disclosure. It details the default behavior (only releases up_tunnel pin, returns remaining_holders), the effect of 'force=true' (drains pools, closes unconditionally), and the consequence for subsequent queries (recreates pools). This is comprehensive for a two-operation tool.
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 long, front-loaded with the primary purpose, and every clause adds value. It is concise without omitting important behavioral details.
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 no output schema, so the description indirectly covers return behavior by mentioning 'remaining_holders'. It covers input, behavior, and side effects adequately for a simple mutation. A minor gap is the lack of explicit mention of the return format (e.g., JSON object with remaining_holders).
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?
Input schema coverage is 100%, so the description adds meaningful context beyond the schema. It explains that 'tunnel_id' is returned by 'up_tunnel' and elaborates on the 'force' parameter's conditional behavior. The description enriches the understanding of parameter usage.
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 identifies the action ('Close a tunnel'), the resource ('previously opened with up_tunnel'), and the key identifier ('tunnel_id'). It distinguishes from the sibling tool 'up_tunnel' by specifying it is the inverse operation.
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 explains when to use the tool (to close a tunnel) and contrasts with 'up_tunnel'. It also describes the default behavior versus the 'force=true' option. However, it does not explicitly state when NOT to use the tool or provide alternatives among siblings.
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?
No annotations provided, but description fully discloses file path resolution (relative, absolute, ~), parent directory creation, overwrite behavior, and dialect-specific streaming vs buffering with row caps (redshift/mssql 100k). No contradictions.
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?
Two sentences, no wasted words. Front-loaded with purpose and use case, followed by key behavioral details in a single compact sentence. Very efficient.
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?
Covers main behavioral aspects for a file-export tool: use case, path handling, dialect differences. However, it does not specify what the tool returns (e.g., success message or file path) despite no output schema. For a write command, the outcome is the file itself, so this is a minor gap.
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 has 100% coverage, so baseline is 3. Description adds value by explaining file_path resolution rules, format default from extension, and overwrite default false. Also mentions dialect-specific row caps which relate to max_rows parameter.
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?
Description clearly states it executes a SQL query and writes result to CSV/JSONL file, distinguishing from the sibling 'query' tool by explicitly mentioning 'instead of returning rows'. The use case for large exports is specified.
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?
Description explicitly says to use for large exports not going through model context, implying alternatives. It details file path rules, overwrite behavior, and dialect-specific row limits. No explicit when-not-to-use but the context is sufficient.
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?
The description fully discloses all behavioral aspects: it resolves secrets, opens tunnels, connects, and runs a query. It explains the return format (ok=true/false with details) and explicitly states that an unreachable database is a valid result, not a tool error. No annotations are provided, so the description carries the full burden and does so excellently.
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: first defines the action, second describes the return. No wasted words, front-loaded with key information, and easy to parse.
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 no output schema, the description thoroughly explains what the tool returns (ok=true with version, user, database, latency; or ok=false with code and hint). It covers all aspects of the tool's behavior, parameter nuances, and error handling, leaving no gaps.
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 coverage is 100%, so baseline is 3. The description adds value by explaining when the database parameter is required ('when the connection declares multiple databases'), which goes beyond the schema description.
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 tests a configured connection end-to-end, specifying the steps: resolves secrets, opens tunnel if configured, connects, runs a server-info query. It distinguishes from sibling tools like connection_list and connection_find by focusing on testing a single connection's functionality.
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 the tool (testing a connection) and explains that an unreachable database is a valid test result. However, it does not explicitly compare to alternatives like query or up_tunnel, though the purpose is distinct.
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?
With no annotations, the description must convey behavioral traits. It mentions a 'live health probe' and describes output fields (tunnel_id, connections, pins), indicating it's a read-only operation. No side effects are suggested, but it could be more explicit about idempotency or rate limits.
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?
Two sentences, no waste. The main action is front-loaded, and additional context about related tools and fields is provided efficiently.
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 parameterless list tool with no output schema, the description sufficiently covers what it does and what the output contains. It references sibling tools to fill context, making it complete for the agent to select and invoke correctly.
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 schema description coverage is 100%. Baseline for 0 params is 4, and the description does not need to add parameter details. It adds value by explaining what the output contains.
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 'List the tunnels currently open in THIS MCP instance' with a specific verb and resource. It distinguishes from sibling tools by mentioning connection_list for configured-but-not-open tunnels, and clarifies how fields relate to other tools like down_tunnel and up_tunnel.
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?
Provides explicit guidance on when to use this tool (to see open tunnels) and points to connection_list as an alternative for configured-but-not-open tunnels. It also explains the meaning of 'connections' and 'pins' in relation to other tools, helping the agent choose correctly.
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?
No annotations provided, so description carries full burden. It discloses reuse behavior, return values (local host/port and tunnel_id), tunnel closure mechanisms (down_tunnel, idle timeout, exit), and exact port binding behavior including failure conditions.
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?
Two sentences, front-loaded with core purpose, followed by lifecycle and optional parameter details. Every sentence adds value with no 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?
With no output schema, description explains return values. Covers lifecycle, parameter behaviors, and constraints. With 9 sibling tools, context is adequate and sufficient.
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?
Schema coverage is 100% with descriptions. The description adds meaningful context: 'connection' requires a tunnel configured, 'local_port' default is config or random, and failure conditions if already open on different port or port taken.
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 specifies a clear verb ('Open or reuse') and resource ('tunnel configured for a connection'), and differentiates from sibling tools like 'down_tunnel' and 'tunnel_list' by stating it does not connect to the database and returns a tunnel_id for later use.
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 (without connecting to the database) and provides conditions for the optional parameter 'local_port' (fails if port taken or already open on different port). It mentions lifecycle: tunnel closed by down_tunnel, idle timeout, or exit, but does not directly compare to siblings like 'tunnel_list' or 'down_tunnel'.
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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