rfcxml-mcp

Server Quality Checklist

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Latest release: v0.4.5
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific aspects of RFC analysis, with no overlap in functionality. For example, get_definitions extracts terms, get_requirements extracts normative language, and get_rfc_structure provides metadata, making misselection unlikely.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as get_definitions, validate_statement, and generate_checklist. This predictability enhances readability and usability for agents.
Tool Count5/5
With 7 tools, the server is well-scoped for RFC analysis, covering key operations like extraction, validation, and dependency mapping. Each tool earns its place without feeling excessive or insufficient for the domain.
Completeness4/5
The toolset provides comprehensive coverage for analyzing RFCs, including structure, definitions, requirements, and dependencies, with minor gaps such as lacking tools for editing or updating RFC content, but core workflows are well-supported.
Average 3/5 across 7 of 7 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
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the basic action without disclosing behavioral traits. It doesn't cover permissions, rate limits, output format, pagination, or error handling, which are critical for a tool with two required parameters and no output schema.
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 a single, efficient sentence that front-loads the core action. It avoids redundancy but is overly brief, potentially sacrificing clarity for conciseness, as it could benefit from slightly more detail without becoming verbose.
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 complexity (2 required parameters, no annotations, no output schema), the description is incomplete. It lacks details on what 'related sections' entails, how results are returned, or error cases, leaving significant gaps for the agent to operate effectively.
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 (RFC number and base section number). The description adds no additional meaning beyond implying a relationship between the parameters, but it doesn't clarify syntax or constraints, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get sections related to the specified section' clearly states the action (get) and resource (sections), but it's vague about what 'related' means—whether by content, structure, or dependencies. It doesn't differentiate from siblings like 'get_rfc_dependencies' or 'get_rfc_structure', leaving ambiguity in purpose.
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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., after retrieving an RFC), or exclusions, leaving the agent to guess based on tool names alone without explicit direction.
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 'Get term definitions from RFC,' which implies a read-only operation, but it doesn't disclose any behavioral traits such as authentication needs, rate limits, error handling, or what the return format looks like. For a tool with no annotations, 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 extremely concise and front-loaded: 'Get term definitions from RFC.' It's a single sentence that directly states the tool's purpose without any unnecessary words or fluff. Every part of the sentence earns its place, making it efficient and easy to parse.
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 complexity of the tool (2 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral aspects, usage context, and what to expect in return, which are crucial for an agent to invoke the tool correctly. Without annotations or an output schema, the description should provide more context to compensate, but it doesn't.
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 100% description coverage, with clear parameter descriptions: 'RFC number' and 'Search for specific term.' The description adds no additional meaning beyond what the schema provides, as it doesn't explain parameter usage, constraints, or examples. With high schema coverage, the baseline score is 3, reflecting adequate but not enhanced parameter semantics.
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 term definitions from RFC.' It specifies the verb ('Get') and resource ('term definitions from RFC'), making it easy to understand what the tool does. However, it doesn't differentiate from sibling tools like 'get_related_sections' or 'get_rfc_structure', which might also retrieve RFC content, so it doesn't achieve full sibling differentiation.
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, exclusions, or comparisons to sibling tools such as 'get_related_sections' or 'get_requirements', leaving the agent without usage instructions. This lack of guidance makes it harder to select the correct tool in a set of similar options.
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 what the tool returns ('section hierarchy and metadata') but doesn't cover critical aspects like whether it's a read-only operation, potential rate limits, authentication needs, error conditions, or response format. This leaves significant gaps in understanding how the tool behaves.
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—a single sentence that directly states the tool's purpose without any fluff. It's front-loaded and wastes no words, making it easy to parse quickly.
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 lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'section hierarchy and metadata' entails in the response, nor does it address behavioral aspects like safety or performance. For a tool with no structured context, more descriptive detail is needed to guide effective 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?
The schema description coverage is 100%, with both parameters clearly documented in the input schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema (e.g., it doesn't explain what 'section hierarchy' means in relation to the parameters). 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 tool's purpose with specific verbs ('Get') and resources ('RFC section hierarchy and metadata'), making it immediately understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'get_related_sections' or 'get_rfc_dependencies', which might have overlapping functionality.
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. With siblings like 'get_related_sections' and 'get_rfc_dependencies' available, there's no indication of how this tool differs or when it's the appropriate choice, leaving usage decisions ambiguous.
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 validates compliance but doesn't describe what the validation entails (e.g., returns a boolean, detailed report, or error messages), whether it requires network access, or any rate limits. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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's front-loaded and wastes no space, making it easy to understand at a glance.
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 complexity (validation operation with no annotations and no output schema), the description is incomplete. It doesn't explain what the tool returns (e.g., pass/fail result, detailed feedback), how validation is performed, or any behavioral traits. This makes it inadequate for an agent to use the tool effectively without guesswork.
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 100% description coverage, with clear parameter definitions. The description adds minimal value beyond the schema by implying the 'statement' parameter is for validation, but it doesn't provide additional context like format examples or validation criteria. Baseline 3 is appropriate as 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 with a specific verb ('validate') and resource ('statement'), specifying it checks compliance with RFC requirements. However, it doesn't explicitly differentiate from sibling tools like 'get_requirements' or 'get_definitions', which might provide related information without validation.
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 prerequisites, context for validation, or how it differs from sibling tools such as 'get_requirements' (which might list requirements) or 'generate_checklist' (which might create validation steps).
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 generates a checklist, implying a read-only operation, but doesn't cover aspects like whether it requires network access, has rate limits, or what the output looks like beyond 'Markdown format'. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded: a single sentence that directly states the tool's purpose and output format. Every word earns its place with no redundancy or unnecessary details, making it efficient for quick understanding.
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 moderate complexity (4 parameters, no output schema, no annotations), the description is minimally adequate. It covers the core purpose but lacks details on behavior, usage context, and output specifics. With no output schema, it doesn't explain return values, leaving gaps that could hinder effective use by an agent.
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 description adds no parameter semantics beyond what the input schema provides. Since schema description coverage is 100%, the schema already fully documents all parameters (rfc, role, sections, includeSubsections). The description doesn't explain how parameters interact or provide additional context, so it 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 tool's purpose: 'Generate RFC implementation checklist in Markdown format.' It specifies the verb ('Generate'), resource ('RFC implementation checklist'), and output format ('Markdown format'), making it unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_requirements' or 'get_rfc_structure', which might also involve RFC content, so it doesn't reach the highest 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 sibling tools or contexts where other tools might be more appropriate, such as using 'get_requirements' for raw requirements instead of a formatted checklist. Without any usage context or exclusions, the agent has minimal guidance.
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 but only states what the tool does, not how it behaves. It doesn't disclose whether this is a read-only operation, what format the relationships are returned in, whether there are rate limits, or what happens with invalid RFC numbers.
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 with zero wasted words. It's appropriately sized for this simple tool and front-loads the core purpose immediately.
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 read operation with 2 parameters and no output schema, the description is minimally adequate. However, without annotations or output schema, it should ideally provide more behavioral context about what's returned and any constraints.
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 completely. The description adds no additional parameter information beyond what's in the schema, maintaining the baseline score 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 ('RFC reference relationships') with specific relationship types ('normative/informative'). It distinguishes from sibling tools like 'get_rfc_structure' by focusing on dependencies rather than structure, but doesn't explicitly contrast with 'get_related_sections' which might have overlapping functionality.
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?
No guidance is provided about when to use this tool versus alternatives like 'get_related_sections' or 'get_requirements'. The description implies it's for dependency analysis but doesn't specify 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral context. It mentions extraction to structured format but doesn't disclose what that format is, whether there are rate limits, authentication needs, or how errors are handled. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without unnecessary words. It's front-loaded with the main 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 tool with 3 parameters, no annotations, and no output schema, the description is adequate but incomplete. It covers the purpose well but lacks details on behavioral traits, output format, and usage context. Given the complexity and missing structured data, it should provide more guidance 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 three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining how filtering works or providing examples. 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.
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 ('Extract'), resource ('normative requirements from RFC'), and format ('structured format'). It distinguishes from siblings by focusing on requirement extraction rather than checklist generation, definition retrieval, or structural analysis.
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 the phrase 'normative requirements (MUST/SHOULD/MAY)', suggesting it's for extracting specific requirement types from RFCs. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_definitions' or 'get_related_sections', nor does it mention prerequisites or exclusions.
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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