Informix MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'get-tables' has a clearly distinct and singular purpose, making it impossible for an agent to misselect between multiple options.
Naming Consistency5/5The naming follows a consistent verb_noun pattern with 'get-tables', and since there is only one tool, there is no inconsistency to evaluate. The naming is clear and predictable within this minimal set.
Tool Count2/5A single tool for a database server is too few for the apparent scope, as it lacks basic CRUD operations, querying, or other database management functions. This severely limits the server's utility and feels incomplete for a database domain.
Completeness1/5The tool surface is severely incomplete for a database server, covering only table listing without any operations for data retrieval, insertion, updates, deletions, schema modifications, or other essential database interactions. This creates significant gaps that will cause agent failures in typical database workflows.
Average 3.1/5 across 1 of 1 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Get all tables', which implies a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns paginated results, or handles errors. For a tool with zero annotation coverage, this leaves significant behavioral aspects unclear.
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, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core functionality without unnecessary elaboration, which is ideal for a simple tool like this.
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?
For a simple read operation with one parameter and no output schema, the description is adequate but lacks depth. It covers the basic purpose but misses behavioral details like response format or error handling. Without annotations or an output schema, the description should ideally provide more context about what 'Get all tables' entails, but it meets the minimum viable threshold.
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?
The schema description coverage is 100%, with the single parameter 'database' clearly documented in the schema. The description adds no additional meaning beyond what the schema provides, as it doesn't elaborate on parameter usage or constraints. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('all tables in the database'), making the tool's purpose immediately understandable. It's specific enough to distinguish it from potential siblings like 'get-table' or 'create-table', though no actual siblings exist in this context. The description avoids tautology by not just restating the name 'get-tables'.
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 provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. It simply states what the tool does without indicating scenarios where it's appropriate or inappropriate. Since there are no sibling tools mentioned, the lack of differentiation is less critical, but overall usage guidance is minimal.
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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