MCP SQL Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: connect_database establishes a connection, describe_table provides schema details, disconnect_database ends the connection, execute_query runs SQL commands, and list_tables enumerates available tables. The descriptions make it easy to differentiate between connection management, metadata exploration, and query execution.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., connect_database, describe_table, disconnect_database, execute_query, list_tables). This uniformity makes the set predictable and easy to understand, with no deviations in naming style.
Tool Count5/5
With 5 tools, the server is well-scoped for its SQL database management purpose. Each tool earns its place by covering essential operations: connection handling, table listing, schema description, query execution, and disconnection. This count is neither too sparse nor bloated for the domain.
Completeness4/5
The tool set provides solid coverage for core SQL operations, including connection lifecycle and basic querying. However, there are minor gaps, such as the lack of tools for managing database objects (e.g., create_table, drop_table) or handling transactions, which agents might need to work around for more advanced tasks.
Average 3.4/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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 provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves schema information, which implies a read-only operation, but doesn't specify details like whether it requires authentication, returns error messages for invalid tables, or provides metadata format (e.g., column types, constraints). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded with the key action ('Get schema information'), making it easy to parse. Every part of the sentence earns its place by specifying the resource and scope.
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?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, and output format. Without annotations or an output schema, the description should ideally provide more context about what 'schema information' includes, but it meets the minimum for a simple read operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'tableName' fully documented in the schema. The description adds no additional parameter details beyond what the schema provides (e.g., examples of table names, format requirements). Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 action ('Get schema information') and target resource ('for a specific table'), making the purpose immediately understandable. It distinguishes from siblings like 'list_tables' (which lists tables) and 'execute_query' (which runs queries), though it doesn't explicitly mention this differentiation. The description avoids tautology by not just restating the name '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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a connected database via 'connect_database'), exclusions (e.g., not for querying data), or comparisons to siblings like 'list_tables' (for table names) or 'execute_query' (for data retrieval). Usage is implied from the purpose but not explicitly stated.
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 for behavioral disclosure. While 'Disconnect' implies a state change, the description doesn't specify whether this is reversible, what happens to active queries/sessions, whether authentication is required, or any side effects. It provides minimal behavioral context beyond the basic action.
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's front-loaded with the core action and resource, making it immediately understandable. Every word earns its place in conveying the essential 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?
For a state-changing operation with no annotations and no output schema, the description is insufficient. It doesn't explain what 'disconnect' entails operationally, what happens after disconnection, whether there are confirmation steps, or what the agent should expect. Given the complexity of database connection management, more context is needed.
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 schema description coverage is 100% (empty schema). The description appropriately doesn't discuss parameters since none exist. This meets the baseline expectation for parameterless tools.
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 action ('Disconnect') and target resource ('current database'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'connect_database' or 'execute_query', but the verb 'Disconnect' inherently distinguishes it from other database operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 or what conditions must be met before disconnecting. It doesn't mention prerequisites (e.g., must be connected first), consequences of disconnecting, or when this operation is appropriate versus maintaining a connection.
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 carries the full burden of behavioral disclosure. It states the tool lists tables, implying a read-only operation, but doesn't specify whether this requires specific permissions, what the output format looks like (e.g., list of names, metadata), or if there are limitations like pagination or rate limits. The description is minimal and misses key behavioral details for a tool with zero annotation coverage.
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, efficient sentence that front-loads the core purpose ('List all tables') with necessary context ('in the connected database'). There is zero waste—every word contributes directly to understanding the tool's function, making it highly concise and well-structured.
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?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is adequate but has gaps. It covers the basic purpose and implies a read operation, but lacks details on output format, permissions, or behavioral traits. Without annotations or output schema, the description should do more to compensate, but it's minimally viable for this simple 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?
The tool has 0 parameters, and schema description coverage is 100% (though empty). The description doesn't need to add parameter details, as there are none to document. It appropriately focuses on the tool's purpose without redundant parameter explanations, meeting the baseline for zero parameters.
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 action ('List') and resource ('all tables in the connected database'), making the purpose immediately understandable. It distinguishes from siblings like 'describe_table' (details about specific tables) and 'execute_query' (general queries), though it doesn't explicitly mention these distinctions. The description avoids tautology by not just restating the tool name.
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 when needing to see all tables, but provides no explicit guidance on when to use this tool versus alternatives like 'describe_table' or 'execute_query'. It mentions the prerequisite of a 'connected database', which hints at needing 'connect_database' first, but lacks clear when/when-not instructions or named alternatives.
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 states the action and return purpose ('Returns query results'), it lacks critical behavioral details such as whether this tool can execute both read and write queries, what permissions are required, potential rate limits, error handling, or transaction implications. For a database query tool with zero annotation coverage, this leaves significant gaps.
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 consists of two concise, front-loaded sentences that efficiently convey the core functionality and outcome. Every word earns its place with zero redundancy or unnecessary elaboration, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (executing arbitrary SQL queries) and the absence of both annotations and an output schema, the description is moderately complete. It covers the basic purpose and return intent but lacks details on result format, error conditions, security implications, and behavioral constraints that would be crucial for safe and effective use.
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 100%, so the schema already fully documents both parameters (query and params). The description adds no additional parameter semantics beyond what the schema provides, such as SQL dialect specifics, parameter binding syntax, or query validation rules. The baseline score of 3 reflects adequate but minimal value addition.
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 specific action ('Execute a SQL query') and target resource ('on the connected database'), distinguishing it from sibling tools like connect_database, describe_table, list_tables, and disconnect_database. It provides a complete verb+resource+scope combination.
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 context through 'on the connected database', suggesting this tool should be used after establishing a connection (likely via connect_database). However, it doesn't explicitly state when to use this vs. alternatives like describe_table or list_tables, nor does it provide exclusions or prerequisites beyond the implied connection requirement.
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 explains the fallback to environment variables and SSL usage, which adds useful context. However, it lacks details on error handling, connection persistence, timeouts, or authentication requirements beyond basic parameters, leaving gaps in behavioral understanding.
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 appropriately sized and front-loaded with the core purpose. Each sentence adds necessary information about parameter sourcing and environment variables without redundancy. It could be slightly more structured by separating concerns (e.g., parameter vs. env var details), but it remains efficient.
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?
Given the complexity of a database connection tool with 7 parameters, no annotations, and no output schema, the description is moderately complete. It covers parameter sourcing and basic usage but lacks details on return values, error cases, or connection lifecycle, which are critical for such an operation. The absence of output schema exacerbates this 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 description coverage is 100%, so the schema already documents all parameters. The description adds value by explaining the environment variable mappings (e.g., DB_TYPE, POSTGRES_HOST, MYSQL_HOST) and the optional nature of parameters, which clarifies usage beyond the schema's basic descriptions. It does not fully detail parameter interactions or validation rules.
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 ('Connect to a PostgreSQL or MySQL database') and specifies the resource (database), making the purpose explicit. It distinguishes from sibling tools like 'execute_query' or 'list_tables' by focusing on establishing a connection rather than querying or metadata operations.
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 on when to use this tool (to connect to a database) and how parameters can be sourced (directly or from environment variables). However, it does not explicitly state when not to use it or mention alternatives like using existing connections from other tools, which prevents a perfect score.
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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