simple-db-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
The tools are mostly distinct: list_schemas, list_tables, describe_table, execute_query, and explain_query each target a different aspect of database exploration. The health, version, and ping_database tools have overlapping purposes around server status, but their descriptions clarify the differences, so only minor confusion is possible.
Naming Consistency4/5
Most tool names follow a clear verb_noun pattern (list_schemas, ping_database, execute_query). However, 'health' and 'version' are bare nouns, deviating from the otherwise consistent style. The underscore convention is uniform throughout, keeping the naming readable.
Tool Count5/5
With 8 tools, the server is well-scoped for a simple database MCP. Each tool covers a necessary function—server diagnostics, schema/table introspection, and query execution/planning—without unnecessary bloat or skimping.
Completeness5/5
For a read-only database tool, the surface is complete: users can discover schemas, explore tables and columns, run queries, and inspect query plans. Health and version cover server metadata. No obvious gaps exist for the intended read-only scope.
Average 3.4/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It simply restates the tool's name in a sentence, adding no details about side effects, permissions, error handling, or safety characteristics beyond the implicit read-only nature of 'list'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence that is easily parsed, but it is under-specified. While concise, it omits necessary parameter context, making it insufficiently informative for an agent to fully utilize the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists, the tool has one optional parameter that is completely unexplained, and there are no annotations. For a tool with low complexity, the description fails to provide the context needed for correct invocation, especially regarding the 'database' parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one optional parameter 'database' with 0% description coverage, and the description makes no mention of it. The agent receives no guidance on how to use the parameter, its meaning, or the effect of the default null value.
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 the specific verb 'List' and identifies the resource as 'available database schemas', clearly distinguishing this tool from siblings like list_tables and describe_table. It precisely states what the tool does without ambiguity.
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 usage for enumerating schemas but does not explicitly state when to use it versus alternatives or mention any exclusions. Context is minimal, relying on the obvious purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only mentions 'read-only,' which suggests safety, but it does not state whether the query is actually executed, what permissions are required, or any side effects. The behavior of generating a plan without executing is implied but not explicit.
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, front-loaded sentence with no redundant words. It efficiently conveys the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the output schema exists and return values need not be explained, the description lacks usage guidelines and parameter semantics. With no annotations and minimal parameter documentation, the overall context is incomplete for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the 'sql' or 'database' parameters. The parameter names are self-explanatory to some degree, but there is no guidance on how 'database' is used or what values are valid, leaving ambiguity.
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 'Return the database query plan for a read-only SQL query' clearly specifies the verb+resource (return the query plan) and distinguishes the tool from siblings like execute_query by focusing on the plan rather than execution results.
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 phrase 'for a read-only SQL query' implies the tool is intended for read-only queries, but there is no explicit statement of when to use this tool versus execute_query or other siblings. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds the context 'configured', indicating it uses default settings, but it does not disclose what happens on failure (e.g., error vs. return value) or whether any state is changed. For a simple ping-style tool, this is adequate but not rich.
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, tightly worded sentence that immediately conveys the tool's purpose. No fluff or repetition, and it is front-loaded with the key action.
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?
For a simple tool with an output schema, the description is nearly sufficient, but it leaves the optional parameter unexplained and does not clearly distinguish from 'health'. A short mention of the parameter or a comparison to 'health' would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema shows a single optional 'database' parameter with no description, and the tool description does not mention this parameter at all. Schema description coverage is 0%, and the description does not compensate by explaining what values the parameter accepts or how it affects behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Verify') and resource ('configured database connection'), making the purpose understandable. However, it does not explicitly differentiate from the sibling tool 'health', which might also verify connectivity, so it falls short of a 5.
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 by the purpose: use it to check that the database connection works. However, there is no explicit guidance about when to choose this over the 'health' tool or any exclusions/alternatives, leaving room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. The phrase 'describe columns and primary key metadata' implies a read-only operation and specifies the output, which provides some transparency. However, it does not explicitly state that no data is modified, nor does it mention error handling or permission requirements. For a read-only metadata tool, the lack of such warnings is less critical, so a mid-range score is appropriate.
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: 'Describe columns and primary key metadata for a table.' It is front-loaded with the verb and resource, contains no redundant words, and is appropriately sized for the tool's simplicity. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists (so return values are covered), the description lacks essential context: it does not explain the optional schema/database parameters, provide usage guidance versus sibling tools, or mention any behavioral caveats. For a tool with three parameters, this is incomplete. The description only covers the core purpose, not the full context needed for correct invocation.
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%, so the description must compensate. The description only mentions 'table' in the context of 'a table', but the 'schema' and 'database' parameters are not explained at all. Users are left to guess what these mean (e.g., database schema vs. JSON schema) and whether they are required for table qualification. The description adds minimal value beyond what a user could infer from the parameter names.
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 ('describe') and the resource ('table'), specifying the exact metadata returned ('columns and primary key metadata'). This distinguishes it from sibling tools like list_tables (which list tables) and explain_query (which explains queries). A specific verb and resource make the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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, nor any context about prerequisites, connection requirements, or when schema/database qualification is needed. It simply states what the tool does, leaving the agent to infer usage from the name and sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool is read-only and applies a row limit, which gives important safety and behavior context. However, it omits other behavioral details such as error behavior, database selection logic, or implications of the limit (e.g., what happens when exceeded). This is a moderate amount of transparency but not complete.
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, front-loaded sentence with no redundancy. It delivers the essential action and a key constraint efficiently. Every word earns its place, making it highly concise.
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?
For a simple query tool with an output schema, the description captures the core function. However, given no annotations and low parameter semantics, it falls short of full completeness. It does not mention parameterization, database routing, or any exception handling, leaving the agent to infer important details from the schema alone.
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?
The schema has 0% description coverage, so the description must compensate. It only clarifies the 'limit' parameter via 'configured row limit'. The 'sql' parameter is implied by 'SQL query', but the 'database' parameter is entirely unexplained. With three parameters, this coverage is insufficient to make the tool safe and easy to invoke correctly.
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 'Execute a read-only SQL query with a configured row limit' clearly identifies the verb (execute), the resource (SQL query), and adds a distinguishing scope (read-only, row limit). This differentiates it from sibling tools like list_tables or explain_query that have more specific purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention that general arbitrary queries go here, while specialized operations like listing schemas or explaining query plans should use their respective tools. There is no explicit 'use for X, not for Y' context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It explicitly states the read-only behavior of listing tables and views, but does not disclose default behavior when schema/database params are omitted or potential error 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?
One terse sentence, front-loaded with the key action, no unnecessary 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?
A simple tool with an output schema; the description adequately conveys the core purpose, though it does not explain default behavior when no parameters are provided (schema defaults to null).
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%. The description only clarifies the 'schema' parameter (listing in a schema) but provides no meaning for the 'database' parameter, which remains ambiguous.
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 verb 'List' and resource 'tables and views' with scope 'in a schema', distinguishing it from siblings like list_schemas and describe_table.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; does not mention exclusions or when to prefer list_schemas/describe_table.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It adds a useful qualification ('non-sensitive') indicating what data is returned, but it does not disclose potential side effects, failure modes, or details about the 'basic' nature of the health information. The statement is truthful but minimal.
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, clear sentence with no wasted words. It front-loads the action and resource, making it 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 the tool's simplicity (no parameters) and the presence of an output schema, the description sufficiently covers the tool's purpose and scope. No additional return-format explanation is needed because the output schema is available.
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, and the schema describes this completely (100% coverage). The baseline for zero parameters is 4, and the description adds no unnecessary parameter details, which is appropriate.
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 ('Return') and specifies the resource ('basic server health and non-sensitive configuration'), clearly distinguishing this from sibling tools like version or ping_database. It precisely states what the tool does without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like ping_database or version. The description implies it serves as a general health check but does not state exclusions or provide context for choosing this over sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It implies a read-only operation, but it does not explicitly state security implications, potential side effects, or error cases. For a simple version endpoint, this is adequate but lacks explicit safety disclosure.
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, concise sentence that directly conveys the tool's purpose. Every word earns its place with no unnecessary detail.
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 simplicity and the presence of an output schema, the description is fully sufficient. It explains what the tool does without needing to elaborate on return values, which are presumably defined by the 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?
The tool has zero parameters, and the description adds no parameter information. The baseline for 0 parameters is 4, and since there is nothing to compensate for, this score is appropriate.
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 function: returning the server name and version. It uses a specific verb ('Return') and identifies a distinct resource from sibling tools like health or ping_database, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 the sibling tools (e.g., health or ping_database). The description only states what it does, not when it is appropriate or how it differs in use cases.
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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