EPA Envirofacts MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap. The environmental_summary_by_location provides a comprehensive overview, get_chemical_release_data focuses on TRI chemical releases, get_facility_compliance_history_tool handles compliance history, search_facilities_tool searches for facilities, and health_check is a system utility. The descriptions clearly differentiate their scopes and use cases.
Naming Consistency3/5
The naming is mixed with some inconsistencies. environmental_summary_by_location and get_chemical_release_data follow a verb_noun pattern, but get_facility_compliance_history_tool and search_facilities_tool append '_tool' unnecessarily, and health_check is a simple compound. While readable, the deviation from a single convention reduces predictability.
Tool Count5/5
With 5 tools, this is well-scoped for an EPA data server. Each tool serves a distinct and essential function: summary, chemical data, compliance, facility search, and health check. The count is appropriate, avoiding both thin coverage and bloat, and aligns with the server's purpose of providing environmental data access.
Completeness4/5
The tool set covers core EPA data domains well, including summaries, chemical releases, facility compliance, and facility search, with no dead ends. A minor gap exists in lacking update or delete operations, but this is reasonable for a read-only data server. Agents can effectively query and analyze environmental data without significant workarounds.
Average 3.7/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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

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 of behavioral disclosure. It mentions the tool returns 'Health status information including EPA API connectivity,' which implies a read-only, non-destructive operation. However, it lacks details on response format, error handling, rate limits, or authentication needs—leaving behavioral 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence and follows with output details. It's efficient with two sentences and minimal waste, though the second sentence could be integrated more smoothly (e.g., 'Returns health status information, including EPA API connectivity').
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 (0 parameters, no annotations, but an output schema exists), the description is reasonably complete. It explains what the tool does and what it returns, and since an output schema is present, it needn't detail return values. However, it could better address behavioral aspects like error cases or typical use contexts.
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 appropriately avoids discussing parameters, focusing instead on the tool's purpose and output. This meets the baseline for tools with no parameters, as it doesn't add unnecessary details.
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 as a 'System health and API connectivity check' with specific verbs ('check') and resources ('System health', 'EPA API connectivity'). It distinguishes itself from sibling tools focused on environmental data retrieval, but doesn't explicitly contrast with hypothetical alternative health-check tools.
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. While it's implicitly for monitoring system/API status, there's no explicit context about prerequisites, timing (e.g., during troubleshooting), or comparisons to other diagnostic tools. It merely states what it does without usage instructions.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool 'Provides environmental summary' but doesn't specify whether this is a read-only operation, potential rate limits, data freshness, or error conditions. The description is functional but lacks critical behavioral context 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose first, followed by details. The Args and Returns sections are well-structured. Minor improvement could be made by integrating the parameter explanations more seamlessly rather than as separate sections.
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, the description doesn't need to detail return values. However, for a tool with no annotations and 2 parameters, the description provides adequate purpose and parameter context but lacks behavioral transparency about how the tool operates, which is a significant gap for a data retrieval 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?
With 0% schema description coverage, the description compensates well by explaining both parameters in the Args section: 'location: Address, city, or ZIP code' clarifies the format beyond just 'string', and 'radius_miles: Search radius in miles (default: 5.0)' provides units and default value. This adds meaningful context that the bare schema lacks.
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 specific action ('Get comprehensive environmental data') and resource ('for a location'), distinguishing it from siblings by specifying it provides a multi-faceted environmental summary rather than focused data on chemical releases, compliance history, or facility searches.
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 by listing the types of environmental data included, but doesn't explicitly state when to use this tool versus alternatives like get_chemical_release_data or get_facility_compliance_history_tool. It provides some guidance through the data scope but lacks explicit comparisons or exclusions.
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?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool 'allows searches' and provides parameter details, but doesn't disclose important behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, data freshness, or what happens when no parameters are provided. The mention of 'county: County name (filtered client-side)' is useful context but insufficient for comprehensive transparency.
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?
The description is well-structured with a clear purpose statement followed by detailed parameter explanations. Every sentence adds value, though the 'Returns' section is somewhat redundant given the existence of an output schema. The text is appropriately sized for a 6-parameter tool with no schema descriptions.
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 complexity (6 parameters, 0% schema coverage) and the existence of an output schema, the description is reasonably complete. It thoroughly documents all parameters and their semantics. The main gaps are the lack of behavioral context (no annotations) and no guidance on when to use versus siblings, but the parameter documentation is comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 6 parameters, the description provides excellent parameter semantics. It clearly explains each parameter's purpose, match behavior (partial vs exact), filtering approach, and default values. The description adds substantial meaning beyond the bare schema, fully compensating for the lack of schema descriptions.
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 'Query TRI chemical releases with flexible search parameters' and specifies it provides 'comprehensive chemical release data from the Toxics Release Inventory (TRI)'. It uses specific verbs ('Query', 'search') and identifies the exact resource (TRI chemical releases), distinguishing it from sibling tools that focus on facilities, compliance, or summaries.
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 its siblings. While it mentions 'flexible search parameters', it doesn't explain when this tool is preferred over alternatives like 'search_facilities_tool' or 'environmental_summary_by_location'. There's no mention of use cases, prerequisites, or exclusions.
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 of behavioral disclosure. It adds useful context such as 'intelligent fallback logic' for IDs and default behavior for years, but it does not cover critical aspects like rate limits, authentication needs, or error handling, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose followed by details on retrieval scope, parameters, and returns. Every sentence adds value, but the Args and Returns sections could be integrated more seamlessly into the flow for slightly better structure.
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 complexity (3 parameters, no annotations, but with output schema), the description is fairly complete. It covers purpose, parameter semantics, and return values, and the output schema reduces the need to detail return formats. However, it lacks behavioral details like rate limits or error cases, which would enhance completeness.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics beyond the schema by explaining registry_id accepts FRS or program-specific IDs, program filters as 'TRI' or 'RCRA', and years defaults to 5 with historical context. This compensates well for the lack of schema descriptions, though not exhaustively.
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 with specific verbs ('Get', 'Retrieves') and resources ('compliance and enforcement history for an EPA-regulated facility'), distinguishing it from siblings like environmental_summary_by_location or search_facilities_tool by focusing on historical compliance data rather than summaries or searches.
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 by specifying it retrieves history for EPA-regulated facilities across RCRA and TRI programs, but it does not explicitly state when to use this tool versus alternatives like get_chemical_release_data or provide exclusions. The context is clear but lacks explicit guidance on tool selection.
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 of behavioral disclosure. It adds useful context about the search functionality (e.g., 'uses contains matching' for facility_name) and the data source, but doesn't mention rate limits, authentication needs, or potential errors. The description doesn't contradict annotations (none exist), but could be more comprehensive for a search tool.
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 well-structured and front-loaded with the core purpose, followed by clear sections for arguments and returns. Every sentence adds value: the first states what the tool does, the second specifies requirements, and the parameter/return details are essential given the lack of schema descriptions. No wasted words.
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 6 parameters with 0% schema coverage and no annotations, the description does a good job explaining inputs and outputs. The presence of an output schema means the description doesn't need to detail return values, which it appropriately summarizes. However, for a search tool with multiple filters, more behavioral context (e.g., performance expectations) would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. It successfully adds meaning for all 6 parameters: it explains each filter's purpose (e.g., 'Partial or full facility name'), provides format examples (e.g., 'Two-letter state code'), and notes constraints like '5-digit ZIP code' and the default limit. This goes well beyond the bare schema.
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 searches for EPA-regulated facilities using various filters, specifying the data source (EPA's Facility Registry Service) and the type of resource. It distinguishes from siblings like 'get_facility_compliance_history_tool' by focusing on search rather than compliance history, though it doesn't explicitly name alternatives.
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 provides some usage context by stating 'At least one search parameter must be provided,' which helps avoid empty queries. However, it doesn't specify when to use this tool versus alternatives like 'environmental_summary_by_location' or 'get_facility_compliance_history_tool,' leaving the agent to infer based on tool names alone.
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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