RAGmonsters Custom PostgreSQL MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but 'getMonsterByHabitat' and 'getMonsters' could cause confusion since both retrieve monsters with filtering capabilities. The descriptions clarify that 'getMonsterByHabitat' is for exact habitat matching while 'getMonsters' offers broader filtering, but agents might still misselect between them.
Naming Consistency3/5
The naming is mixed with inconsistent patterns: 'add' uses a generic verb, 'getHabitats' and 'getMonsters' follow a verb_noun plural pattern, while 'getMonsterByHabitat', 'getMonsterById', and 'getMonsterByName' use a verb_noun_preposition format. This creates readability but lacks uniformity across all tools.
Tool Count4/5
With 6 tools, the count is reasonable for a PostgreSQL-based monster database server. It covers core operations like adding data and querying monsters in various ways, though it might benefit from additional tools for updates or deletions to be fully scoped.
Completeness3/5
The tool set covers querying and adding data well, but there are notable gaps for a database server: no update or delete tools for monsters or habitats, and no tool for creating habitats. This limits full lifecycle management and could cause agent failures in more complex workflows.
Average 3.3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Add' implies a simple mathematical operation, it doesn't address potential behavioral traits such as error handling (e.g., overflow), performance characteristics, or any side effects. The description is minimal and lacks necessary context for safe invocation.
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 'Add two numbers' is extremely concise—a single three-word phrase—with zero wasted words. It's front-loaded and directly communicates the core function without any unnecessary elaboration, making it efficient for quick comprehension.
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 simplicity (two numeric parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return value (e.g., sum of the numbers), error conditions, or any behavioral nuances. For even a basic tool, more context is needed to ensure reliable agent 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 0% description coverage, so parameters 'a' and 'b' are undocumented in structured fields. The description 'Add two numbers' implies these parameters are numbers to be added, adding some semantic meaning beyond the schema's type constraints. However, it doesn't specify details like acceptable ranges or units, leaving gaps in parameter understanding.
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 'Add two numbers' clearly states the tool's function with a specific verb ('Add') and resource ('two numbers'), making the purpose immediately understandable. However, it doesn't distinguish this tool from potential sibling tools (like 'multiply' or 'subtract'), which would require explicit differentiation for a perfect score.
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 any context, prerequisites, or exclusions, leaving the agent with no information about appropriate usage scenarios beyond the basic function 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information' but doesn't specify what that includes (e.g., stats, abilities, weaknesses), whether it's a read-only operation, error handling for invalid IDs, or performance characteristics like rate limits. This leaves significant gaps for agent understanding.
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 directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy 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?
For a simple lookup tool with one parameter and no output schema, the description is minimally adequate. However, it lacks details on the returned data structure (e.g., what 'detailed information' entails) and behavioral aspects like error cases, which would help an agent use it correctly. The absence of annotations exacerbates these gaps.
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 schema description coverage is 100%, with the parameter 'monsterId' clearly documented as 'ID of the monster to retrieve'. The description adds no additional semantic context beyond what the schema provides, such as format examples or valid ranges. Given the high schema coverage, the 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 verb ('Get detailed information') and resource ('about a specific monster by ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'getMonsterByName' or 'getMonsterByHabitat', which also retrieve monster information but use different identifiers.
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 sibling tools like 'getMonsterByName' (for name-based lookup) or 'getMonsterByHabitat' (for habitat-based filtering), nor does it specify prerequisites such as needing a valid monster ID.
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 it retrieves a list but doesn't specify if it's read-only, safe, paginated, or has any side effects. For a tool with zero annotation coverage, this is a significant gap in transparency.
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 directly states the tool's function without any fluff. It's appropriately sized and front-loaded, making it easy 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 simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. However, it lacks details on behavioral aspects like safety or output format, which would be helpful for an agent to use it correctly, especially without annotations.
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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is fine here, but it could hint at any implicit constraints (e.g., sorting or limits), though not required. Baseline is high due to no 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 verb ('Get') and resource ('list of all available habitats'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'getMonsterByHabitat' or 'getMonsters', which also retrieve data but with different scopes or filters, so it lacks sibling distinction.
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 scenarios where this tool is preferred over siblings like 'getMonsterByHabitat' (which filters by habitat) or 'getMonsters' (which retrieves monsters instead of habitats), leaving the agent without 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions filtering, sorting, and pagination but doesn't describe important traits like whether this is a read-only operation, what happens with invalid filters, rate limits, authentication requirements, or the format of returned results. For a list retrieval 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 is a single, efficient sentence that front-loads the core purpose ('Get a list of monsters') and then succinctly lists the key capabilities. Every word earns its place with no redundancy or unnecessary elaboration.
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 no annotations and no output schema, the description is incomplete for a tool with four parameters and nested objects. It doesn't explain what the returned list looks like, how errors are handled, or important behavioral aspects like default values or constraints. For a list retrieval tool with filtering capabilities, more context is needed to be fully helpful.
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 documents all four parameters thoroughly. The description adds minimal value by mentioning 'optional filtering, sorting, and pagination' which aligns with the schema but doesn't provide additional semantic context beyond what's already in the parameter descriptions. This meets the baseline for high schema coverage.
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 verb ('Get') and resource ('list of monsters'), making the purpose immediately understandable. It distinguishes itself from siblings like getMonsterById or getMonsterByName by indicating it returns a list rather than a single entity. However, it doesn't explicitly differentiate from getMonsterByHabitat which also involves filtering.
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 through 'optional filtering, sorting, and pagination', suggesting this tool is for general queries rather than specific lookups. However, it doesn't explicitly state when to use this versus alternatives like getMonsterByHabitat or getMonsterById, nor does it provide any exclusions or prerequisites for usage.
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. It discloses key behavioral traits: partial matching and a limit of 5 results, which are valuable beyond basic 'get' functionality. However, it lacks details on error handling, authentication needs, or rate limits, leaving gaps for a tool with no 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 extremely concise and front-loaded: a single sentence that efficiently conveys the core functionality and key constraints. Every word earns its place, with no wasted text or redundancy.
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 complete. It covers the basic operation and behavioral constraints but lacks details on output format or error cases. For a simple lookup tool, this is adequate but leaves room for improvement in contextual richness.
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 documents the 'name' parameter as 'Name of the monster to search for (can be partial).' The description adds no additional meaning beyond this, merely restating 'partial match.' Baseline 3 is appropriate as the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get monsters by name' specifies the verb (get) and resource (monsters). It distinguishes from siblings like getMonsterById and getMonsters by focusing on name-based retrieval. However, it doesn't explicitly differentiate from getMonsterByHabitat, which is a similar lookup but by different criteria.
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 'partial match, returns up to 5 matches,' suggesting it's for fuzzy name searches with result limits. However, it doesn't explicitly state when to use this versus alternatives like getMonsterById (exact ID match) or getMonsters (full list). No guidance on prerequisites or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the 'exact match only' constraint, which is useful behavioral context beyond basic functionality. However, it lacks details on error handling, rate limits, authentication needs, or what the return format looks like (e.g., list of monsters with specific fields).
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 and well-structured: two sentences that efficiently convey purpose and usage guidelines without wasted words. The first sentence states the core functionality, and the second provides critical procedural advice, both earning their place.
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 moderate complexity (2 parameters, no output schema, no annotations), the description is fairly complete. It covers purpose, usage guidelines, and a key behavioral constraint ('exact match only'). However, without annotations or an output schema, it could benefit from more details on return values or error cases, but it's adequate for basic 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 documents both parameters ('habitat' and 'limit') with descriptions. The description repeats the guidance about calling 'getHabitats' for the 'habitat' parameter but doesn't add new semantic meaning beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get monsters by habitat (exact match only).' It specifies the verb ('Get'), resource ('monsters'), and constraint ('by habitat, exact match only'). However, it doesn't explicitly differentiate from siblings like 'getMonsters' (which might fetch all monsters) or 'getMonsterByName' (which filters by name rather than habitat).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'for best results, first call getHabitats to get a list of available habitats, then find the most appropriate one to use with this tool.' This tells the agent when to use this tool (after retrieving habitat list) and references a sibling tool ('getHabitats') as a prerequisite, offering clear alternatives and 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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