Postgres MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct aspect of database interaction: health checks, index analysis, query execution, explain plans, object details, top queries, and listing schemas/objects. There is no overlap; the two index analysis tools are differentiated by input (specific queries vs. workload).
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (analyze_, execute_, explain_, get_, list_). Verbs like 'analyze', 'execute', 'explain', 'get', and 'list' are used uniformly, making the naming predictable.
Tool Count5/5
With 9 tools, the set is well-scoped for a Postgres MCP server covering health analysis, index optimization, query execution, and schema exploration. It neither feels sparse nor overwhelming, earning its place.
Completeness4/5
The tool set covers analysis and ad-hoc queries comprehensively via execute_sql, but lacks explicit tools for creating, altering, or dropping database objects. However, execute_sql enables these operations indirectly, making the gap minor.
Average 3.6/5 across 9 of 9 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- 2 of 19 community issues answered or closed in the last 6 months
- No commit activity data available
- Last stable release on May 16, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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?
While the destructiveHint annotation indicates potential for data modification, the description does not elaborate. It fails to mention that execution may alter data, require authentication, or have side effects like creating temporary tables. The description adds no behavioral context beyond the annotation.
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 very short (5 words) and front-loaded, which aids quick scanning. However, it sacrifices essential details for brevity. A slightly longer description with context would be more useful while still being concise.
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 destructive nature and the presence of an output schema, the description should cover safe usage, default behavior (the default 'all' is unclear), and whether it supports SELECT-only or DDL/DML. The current description leaves significant gaps, making it incomplete for reliable agent 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?
The input schema already includes a description for the 'sql' parameter. The tool description repeats the purpose without adding new parameter meaning. Schema coverage is 100%, so baseline of 3 is appropriate; no extra value is provided.
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 'Execute any SQL query' clearly states the tool's action (execute) and resource (SQL query). It is specific enough to distinguish from sibling tools like analyze_db_health or explain_query, which focus on analysis rather than execution. However, it could be more precise about the scope of supported SQL (e.g., DDL vs DML).
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 gives no guidance on when to use this tool versus its siblings. It does not mention scenarios to avoid (e.g., for resource-intensive queries) or prerequisites (e.g., user permissions). A brief note on appropriate contexts 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 declare readOnlyHint=true, and the description's 'Show detailed information' aligns with a read operation. No contradictions. However, the description adds no extra behavioral context beyond the annotation, but it is consistent.
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 very concise (one sentence), but it lacks structure and could be more informative without being verbose. It is not front-loaded with critical details.
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?
With an output schema present, the description does not need to explain return values. However, it does not specify what kind of details are provided, leaving some ambiguity. Adequate for a simple detail retrieval tool.
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%, so baseline is 3. The description does not add any additional meaning to the parameters beyond their schema definitions.
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 it shows detailed information about a database object, distinguishing it from sibling tools like list_objects (which lists objects) and list_schemas (lists schemas). However, it does not specify what 'detailed information' includes, but it is specific enough.
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 when-to-use or when-not-to-use guidance is provided. There is no mention of alternatives or contexts where this tool is preferred over siblings.
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 agent knows it's a safe read. The description adds context by specifying the data source (pg_stat_statements) which implies the extension must be enabled, but does not detail potential impacts like query reset or permission requirements.
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, no unnecessary words. Clear and to the point. Could be slightly improved by adding a brief note about extension requirement, but remains appropriately sized.
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 and optional parameters, the description is adequate but minimal. It does not mention prerequisites (pg_stat_statements must be enabled) or any limitations, which would be helpful for an agent deciding whether to use this tool.
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 both parameters. The overall description reinforces the sort_by options by mentioning 'slowest or most resource-intensive', but adds no new insight beyond what the schema 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 uses a specific verb 'reports' and clearly identifies the resource as 'the slowest or most resource-intensive queries' from 'pg_stat_statements'. It distinguishes from siblings like analyze_query_indexes or explain_query by focusing on top queries by performance metrics.
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 analyze_db_health or execute_sql. The description implies it's for identifying problematic queries but does not explicitly state when not to use it or direct to other 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?
Annotations already indicate readOnlyHint=true, so the read-only nature is clear. The description adds no further behavioral details beyond analyzing queries and recommending indexes. No mention of prerequisites, rate limits, or side effects.
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 sentence that fully captures the tool's purpose with no extraneous words. It is front-loaded and 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 tool has an output schema (not shown) and only 2 parameters, the description minimally covers the core functionality. Missing details like whether recommendations are returned as a list or if any prerequisites exist. Could be more informative.
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%, so the description does not need to explain parameters. It adds no extra meaning beyond what the schema provides for 'method' and 'max_index_size_mb'.
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 it analyzes frequently executed queries and recommends indexes. However, it does not differentiate itself from sibling tool 'analyze_query_indexes', which may have a similar purpose.
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 workload index analysis but provides no explicit guidance on when to use vs. alternatives like 'analyze_query_indexes' or 'explain_query'. No exclusions or context are given.
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 read-only behavior (readOnlyHint: true). The description adds that the tool shows how the database will execute and provides cost estimates, but it does not disclose any additional behavioral traits such as the impact of the 'analyze' parameter or potential performance implications.
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 efficiently conveys the core functionality without unnecessary words. It is front-loaded with the action and resource.
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?
While the description covers the basic purpose, it does not mention optional parameters (analyze, hypothetical_indexes) or their effects. Given the output schema exists, return values are not needed, but the description could be more complete for a tool with three parameters and advanced features.
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 description does not add meaning beyond the input schema, which already has 100% coverage with detailed parameter descriptions. Therefore, it meets the baseline of 3.
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 a SQL query's execution plan with cost estimates. It uses a specific verb ('explains') and resource ('execution plan'), and distinguishes it from sibling tools like execute_sql or analyze_query_indexes.
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 (e.g., when to use explain_query vs. analyze_query_indexes). The description lacks context about prerequisites or scenarios where it's appropriate.
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?
The description is consistent with the readOnlyHint annotation (true) and does not contradict it. However, it adds no behavioral context beyond the annotation. Since annotations carry the behavioral burden, a score of 3 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 short sentence that is efficiently front-loaded and contains no unnecessary words. It earns its place by clearly stating 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?
Given the tool's simplicity and the presence of a detailed input schema and readOnlyHint annotation, the description is sufficient for an AI agent to understand the basic purpose. It could optionally mention the object types listed, but the schema provides that detail. Overall, it is adequately complete.
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% (both parameters have descriptions in the input schema). The tool description adds no additional meaning about parameters. Per criteria, baseline is 3 when schema coverage is high.
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 'List objects in a schema' clearly states the action (list) and resource (objects in a schema). It distinguishes from sibling tools like 'list_schemas' which lists schemas, and 'get_object_details' which details a single object. The verb and resource are specific and 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 usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. It simply states what the tool does without contextual guidance.
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?
The description adds no behavioral details beyond the annotation 'readOnlyHint: true'. Given the simplicity of the operation, this is adequate but does not exceed expectations.
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, no redundant information. Highly concise and front-loaded.
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?
Complete given zero parameters, presence of output schema, and annotation. No additional information is necessary for a simple 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?
The tool has zero parameters, so the description does not need to add parameter semantics. Baseline of 4 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 'List all schemas in the database' clearly states the action (list) and resource (schemas), and it distinguishes this tool from sibling tools like 'list_objects' or 'execute_sql'.
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 alternatives (e.g., when to use 'list_objects' instead). Agent must infer purpose from name alone.
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 behavioral context by specifying the limit of 10 queries and that it recommends indexes, which is valuable beyond the annotations. 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?
The description is a single sentence that is front-loaded with the main action and constraints. Every word is necessary and there is 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?
Given the tool has an output schema, the description does not need to explain return values. The description covers the purpose, input limit, and expected output (index recommendations). For a read-only analysis tool, this is fully sufficient.
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 fully documents the three parameters (queries, method, max_index_size_mb). The description adds minimal extra meaning beyond restating the queries parameter. 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?
The description clearly states the verb 'Analyze', the resource 'a list of SQL queries', and the output 'recommend optimal indexes'. It also includes a specific constraint (up to 10 queries), which distinguishes it from sibling tools like analyze_workload_indexes.
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 small batch of queries to get index recommendations, but it does not explicitly state when to use this tool versus alternatives like analyze_workload_indexes or execute_sql. There are no exclusions or when-not-to-use guidance.
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?
Annotations already declare readOnlyHint=true. Description adds behavioral detail by listing each health check's purpose (e.g., 'checks for invalid, duplicate, and bloated indexes'), which is consistent with read-only analysis.
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?
Description is well-structured with a short opening sentence followed by bullet points listing checks. No wasted words, front-loaded with main purpose.
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 single optional parameter and existing output schema, the description fully explains what the tool does, how to specify checks, and what each check covers.
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% (one parameter fully described). Description adds minor nuance (comma-separated allowed) but does not significantly enhance understanding 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 'Analyzes database health' and lists specific health checks (index, connection, vacuum, etc.), distinguishing it from sibling tools like analyze_query_indexes which focus on specific aspects.
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 clear guidance on how to use the tool: specify a single check or comma-separated list, default 'all'. However, does not explicitly compare to siblings or state when not to use this tool.
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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