mcp-epa-echo
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
With only one tool, there is no risk of confusion between tools. The single tool's purpose is clear and distinct.
Naming Consistency5/5The single tool uses a clear snake_case verb_noun pattern ('get_dmr_values'), which is consistent with itself.
Tool Count2/5A single tool for what appears to be a complex domain (EPA ECHO data) is insufficient. Most well-scoped servers have 3-15 tools to cover basic operations.
Completeness2/5The tool provides access only to DMR values, but the server name suggests a broader scope (EPA ECHO). Missing tools for facility search, permits, compliance, etc., are notable gaps.
Average 4.8/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- Last stable release on
- 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.
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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
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It thoroughly explains key behaviors: the 'windowing trap' with date ranges, handling of zero results, interpretation of null dmrValue with nodiFlag, parameter matching, and result truncation. All behavioral traits are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear paragraphs and warnings. It is somewhat lengthy but each section adds value with no redundancy. Could be slightly more concise, but overall effective.
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?
Given the complexity (6 parameters, no output schema, no annotations, no siblings), the description is remarkably complete. It covers not only the primary function but edge cases (ambiguous names, zero results, null dmrValue), alternative tools, and behavioral nuances. No gaps identified.
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?
Schema description coverage is high (83%), but the description adds significant meaning beyond the schema: the windowing trap, the interaction between startDate/endDate, the substring matching behavior for parameter, and the meaning of nodiFlag. It adds value, though the schema already documents basics.
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 it gets measured DMR values, not limits, and explicitly distinguishes from get_permit_limits. The verb 'get' and resource 'DMR values' are specific, and the distinction from the sibling is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use (getting actual effluent values) and when-not-to-use (for limits, use get_permit_limits). It also gives detailed guidance on facility identification (prefer npdesId, name resolution with fallback), date range usage, filtering, and result limits.
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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- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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