postgres-mcp

Server Quality Checklist

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Latest release: v0.3.0
Disambiguation4/5
Most tools have distinct purposes, but the two index analysis tools (analyze_query_indexes and analyze_workload_indexes) overlap somewhat, though descriptions clarify their different scopes.
Naming Consistency5/5
All tools use consistent snake_case verb_noun naming pattern (e.g., analyze_db_health, execute_sql, list_objects), making it predictable.
Tool Count5/5
10 tools is well-scoped for a database management server, covering health checks, index analysis, SQL execution, query analysis, and object browsing without being excessive.
Completeness4/5
The tool set covers most essential database operations (health, indexing, SQL, query analysis, schema browsing), though minor gaps like user management or lock monitoring exist but are not critical.
Average 3.6/5 across 10 of 10 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
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This repository includes a README.md file.
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{
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  ]
}
```
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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?
The description adds no behavioral information beyond the annotations' destructiveHint: true. It does not disclose potential side effects, timeout limits, or that it can modify or delete data. The annotation bears the entire burden, and the description fails to elaborate.
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 extremely concise (4 words), making it easy to read and parse. However, it lacks structure and could benefit from a sentence about return values or limitations. The brevity is a trade-off.
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?
Given the tool's complexity (executing arbitrary SQL, destructive), the description is insufficient. It omits return format, execution constraints, security implications, and guidance on using with other tools. The presence of an output schema partly compensates, but the description should still provide operational context.
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 covers the single parameter with a description ('SQL to run') and default 'all'. Schema documentation coverage is 100%, so the description adds no additional semantic value. The default 'all' is unclear but not explained in the description.
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 executes SQL queries, which is its core purpose. However, it does not differentiate from sibling tools like explain_query or analyze_db_health, though those are not execution tools. The verb 'execute' and resource 'SQL query' are clear, but the scope ('any SQL') is broad.
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. It doesn't specify prerequisites, whether it's for read-only queries (despite destructiveHint), or when to prefer other tools like execute_sql_file. The description provides no usage context.
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?
The description only states it 'shows' information, which is consistent with the readOnlyHint annotation, but it adds no additional behavioral context such as required permissions, performance implications, or behavior for missing objects. With annotations already declaring read-only, the description provides minimal added value.
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 a single, concise sentence that effectively communicates the main purpose. It is front-loaded and contains no unnecessary words, though it could be slightly more detailed without becoming verbose.
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 presence of an output schema, the description does not need to explain return values. However, it omits context about error handling, required permissions, or potential performance costs. It is adequate for a straightforward tool but not fully comprehensive.
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 coverage is 100%, with descriptions for all three parameters (schema_name, object_name, object_type). The description does not add any extra meaning beyond the schema, so baseline score of 3 is appropriate.
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 shows detailed information about a database object, but it lacks specificity about what 'detailed information' entails, which could include properties, columns, or other metadata. It distinguishes from sibling tools like list_objects and list_schemas by focusing on details of a single object.
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 such as list_objects, explain_query, or analyze_db_health. There is no mention of prerequisites, typical use cases, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, so the safe read behavior is known. Description adds only the schema scoping, no further behavioral details like pagination or results format. Adequate with annotations but not enriched.
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?
Single sentence is very concise but could be slightly more informative. No wasted words, but front-loading is minimal.
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 listing tool with an output schema, the description is minimally adequate. Missing usage guidelines and behavioral details make it incomplete for nuanced decisions.
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% with both parameters documented. Description adds no extra meaning beyond the schema, so baseline score applies.
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 'List objects in a schema' uses a specific verb and resource, clearly distinguishing from sibling tools like list_schemas (lists schemas) and get_object_details (details on a specific object).
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 such as get_object_details or analyze_* tools. Lacks explicit when/when-not 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?
Annotations already indicate readOnlyHint=true. Description adds value by detailing available checks but no further disclosure of behavior (e.g., performance impact, data retrieval). No contradiction.
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?
Description is somewhat lengthy with a bullet list. Could be more concise but is well-structured and front-loaded with purpose.
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?
With only one optional parameter and an output schema, the description covers the essential functionality. Missing usage guidelines but otherwise complete.
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% with description for health_type. Description adds meaning by listing valid values and explaining default and comma-separated usage, though slight inconsistency with schema type.
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 verb 'analyzes' and resource 'database health' are clearly stated. The list of health checks distinguishes it from sibling tools like analyze_query_indexes, which are index-specific.
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 vs alternatives. Lacks context like 'Use this for overall health assessment, use analyze_query_indexes for specific index analysis.'
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?
Annotations include readOnlyHint=true, which the description does not contradict. The description adds no further behavioral details (e.g., performance impact, data source) beyond the core purpose, but the annotation covers safety adequately.
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?
A single, concise sentence that immediately states the tool's action and result. No wasted words, and the structure is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 optional parameters, output schema present), the description is sufficient. It does not need to explain outputs since the output schema exists, and the tool's self-contained nature means no prerequisites are required.
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 covers all parameters with descriptions (100% coverage), so the description's lack of parameter details does not detract. The baseline score of 3 is appropriate as the schema already provides meaning.
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 verb ('Analyze') and resource ('frequently executed queries' and 'recommend optimal indexes'), and it distinguishes itself from siblings like 'analyze_query_indexes' by specifying the focus on workload and recommendations.
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 (e.g., analyze_query_indexes) or when not to use it. It lacks explicit context for usage decisions.
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?
Beyond the destructiveHint annotation, the description adds key behavioral context: the file executes as a single transaction with rollback on failure, and the requirement for unrestricted access mode. This helps the agent understand side effects and constraints.
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 (two sentences) and well-structured: the first sentence states the primary purpose, the second adds critical transactional behavior. No redundant or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (not shown), the description appropriately omits return value details. It covers the core behavior (transaction, rollback, access mode). It could mention error handling (e.g., file not found) but is sufficient for most use cases.
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 already provides 100% coverage for the file_path parameter (description: absolute path). The description does not add further meaning beyond stating the file is a SQL file, which is a minor addition.
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 executes a SQL file for migration/DDL, distinguishing it from inline SQL execution (sibling execute_sql) by specifying file-based input. However, it does not explicitly contrast with siblings.
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 mentions the tool is only available in unrestricted access mode, providing a usage constraint. However, it lacks guidance on when to use this over execute_sql or other alternatives, and no exclusions or prerequisites.
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?
Annotations already provide readOnlyHint: true. Description adds no extra behavioral context (e.g., performance, scope of schemas). With annotations present, the description should at least add that it returns all schemas without filtering.
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?
Single sentence with no extraneous words. Efficiently conveys the tool's purpose.
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?
Has output schema, so return value explanation is not needed. Description is sufficient for a simple list tool with no parameters, but could mention if system schemas are included.
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?
No parameters exist, and schema coverage is 100%. Description adds no parameter info, but given no parameters, a baseline of 3 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?
Description clearly states 'List all schemas in the database', a specific verb and resource. It distinguishes itself from sibling tools (e.g., analyze_db_health, execute_sql) which are analytic or operational.
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?
No explicit guidance on when to use or alternatives. However, the simplicity of the tool makes its usage obvious. A note about when to prefer it over other metadata tools would improve this.
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?
Annotations already declare readOnlyHint=true, so the read-only nature is clear. The description adds context about using pg_stat_statements but does not disclose other behavioral traits like authentication requirements or statistical reset 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 14-word sentence that immediately conveys the tool's function with no unnecessary words. It is appropriately front-loaded and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of a complete input schema and output schema, the description provides sufficient context for this simple reporting tool. It could mention that results are ranked by the chosen sort_by criterion, but the schema covers that.
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 coverage is 100% with detailed descriptions for both parameters (sort_by and limit). The description adds no additional semantic meaning beyond the schema, so baseline score of 3 applies.
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 purpose: 'Reports the slowest or most resource-intensive queries' and specifies the data source ('pg_stat_statements' extension). It distinguishes from sibling tools like analyze_query_indexes which focus on indexing analysis.
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 viewing slow queries but does not provide explicit guidance on when to use this tool vs alternatives (e.g., analyze_db_health) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds that the tool recommends optimal indexes based on the provided queries, with a constraint of up to 10 queries. No behavioral contradictions exist. It provides additional context beyond the annotations, such as the limitation on query count.
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, well-structured sentence that front-loads the core functionality: 'Analyze a list of (up to 10) SQL queries and recommend optimal indexes'. Every part is necessary and no words are wasted.
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 has 3 parameters with complete schema descriptions and an output schema exists, the description covers the essential purpose and constraints. It explains the input (list of queries with a limit) and the output (recommendations). There is no missing information critical for the agent to understand the tool's role.
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 input schema has 100% description coverage, so the baseline is 3. However, the description adds the important constraint that the queries list is limited to 'up to 10', which is not present in the schema description. This adds meaningful context for the 'queries' parameter, improving understanding beyond what the schema alone provides.
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 'Analyze a list of (up to 10) SQL queries and recommend optimal indexes'. It uses a specific verb (analyze) and resource (list of SQL queries), and includes a key constraint (up to 10). This distinguishes it from sibling tool 'analyze_workload_indexes' which likely deals with workloads rather than explicit queries.
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 analyzing a limited set of up to 10 SQL queries, but does not explicitly state when to use this tool versus alternatives. For example, it does not mention when to choose 'analyze_workload_indexes' or other siblings. The context signals show sibling tools, but no guidance on differentiation is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, and the description confirms it explains plans without modification. It adds behavioral detail about the 'analyze' parameter actually running the query for real statistics, which is not in annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The tool description is a single, front-loaded sentence that efficiently conveys the core purpose. Parameter descriptions are appropriately detailed without 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?
Given the presence of an output schema, the description does not need to detail return values. The combination of tool and parameter descriptions fully covers the tool's behavior and inputs.
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%, and the description adds significant value: explains that 'analyze' runs the query, and provides detailed format and examples for 'hypothetical_indexes' 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?
The description clearly states the tool's purpose: explaining execution plans for SQL queries with cost estimates. It distinguishes this from siblings like 'execute_sql' which runs queries, and 'analyze_query_indexes' which focuses on index analysis.
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 execution plan analysis is needed but does not explicitly state when to use over alternatives or when not to use. No mention of prerequisites or exclusions.
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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