pg-mcp-bridge
Server Quality Checklist
Latest release: v1.0.2
- Disambiguation5/5
Each tool has a clear, unique purpose: listing schemas, listing tables, describing columns, running SQL queries, and checking connectivity. There is no overlap or ambiguity.
Naming Consistency5/5All tool names use a consistent snake_case verb_noun pattern, such as list_schemas, list_tables, describe_table, query, and ping. The naming is predictable and uniform.
Tool Count5/5With 5 tools, the server covers all essential operations for a PostgreSQL bridge: schema exploration, table metadata, column details, arbitrary SQL execution, and connectivity checks. The count is well-scoped without unnecessary extras.
Completeness5/5The tool surface is complete for its domain, providing full CRUD-like capabilities through the general query tool, plus necessary introspection tools. There are no obvious gaps; it supports both read and write operations as per access mode.
Average 3.9/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 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
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 bears full responsibility for behavioral disclosure. It only states that the tool lists non-system schemas and that they are accessible via a remote tunnel. It does not mention side effects (likely none), authentication requirements, rate limits, or any other behavioral traits. Critical information is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that is concise and front-loaded. Every word adds value, specifying the action, resource, and scope without any unnecessary verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and no annotations, the description provides the basic purpose but lacks details about the output format (e.g., list of schema names only or with metadata), ordering, or any limitations. It is sufficient for a simple discovery tool but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 meaning beyond the input schema. The schema description coverage is 100%. With no parameters, a baseline score of 4 is appropriate as there is nothing more to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists non-system PostgreSQL schemas available through the remote tunnel. It uses a specific verb (list) and resource (schemas), and the qualifier 'non-system' distinguishes it from system schemas. The sibling tools list_tables, describe_table, query, and ping are all distinct, so there is no confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks explicit guidance on when to use this tool versus alternatives. It only says schemas are available through the remote tunnel, implying they are accessible, but does not explain prerequisites, when to use, or when not to use. No comparisons or usage context is provided.
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 provided. Description only states what is returned, not behavioral traits like read-only nature, permissions needed, or error handling. Does not disclose 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 13 words, concise and front-loaded with the verb. No wasted or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description lists the key information returned (columns, types, etc.). Parameters are fully documented. Adequate for a simple metadata tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described. Description adds no extra meaning beyond the schema; baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Describe' and resource 'table', listing specific details returned (columns, types, nullability, defaults, primary key). Distinguishes from siblings: list_schemas and list_tables list names only, query runs arbitrary SQL.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. Usage is implied from the description, but no mention of alternatives or prerequisites. Siblings exist but not referenced.
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, description states it lists tables and views (read-only), but does not disclose any potential side effects, auth requirements, or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise, front-loaded, and contains no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple tool with one optional parameter; missing output specification but otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers 100% of parameter details (name, type, default, description), so description adds no extra meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'List' and resource 'tables and views', clearly distinguishing from sibling tools like list_schemas (schemas) and describe_table (specific table).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings like describe_table or query; usage is implied but not clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, but description notes it's a connectivity check (non-mutating) and lists returned fields. Could be more explicit about side effects (none).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with purpose, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Comprehensive for a simple health check: no output schema, but lists return fields. No missing context given tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters; schema coverage 100%. Description adds meaning by explaining what the tool does and what it returns.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it checks connectivity and returns specific fields. Distinguishes from siblings which are data retrieval tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies use for checking connectivity before other operations, but no explicit when-to-use 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.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
In the absence of annotations, the description reveals behavioral traits such as varying permissions by access_mode and the single-statement constraint. It implicitly warns about potential destructive actions by mentioning DDL/DML permissions, though it could detail error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: three sentences that front-load the primary action, then detail constraints. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description covers the main functionality and constraints, it lacks details on the return format or error handling, which are not covered by an output schema. For a SQL query tool, knowing the result type would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds meaning by categorizing SQL types by access_mode and linking to ping. It goes beyond the schema's 'permissions enforced' note to provide concrete examples of allowed statements.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a single SQL statement, which is specific to the query action. It distinguishes from siblings like list_schemas and list_tables by focusing on executing arbitrary SQL rather than metadata listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains that allowed statements depend on server access_mode and suggests using ping to check the current mode. It also explicitly limits to one statement per call. While not covering all alternatives, it provides clear usage context.
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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