RFC MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: get_rfc retrieves a full document, get_rfc_section extracts a specific part, and search_rfcs finds documents by keyword. There is no overlap or ambiguity between these functions, making tool selection straightforward for an agent.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with snake_case (get_rfc, get_rfc_section, search_rfcs). The naming is predictable and readable, with no deviations or mixed conventions.
Tool Count5/5With 3 tools, the server is well-scoped for its purpose of accessing RFC documents. Each tool earns its place by covering distinct aspects (fetching, sectioning, searching), and the count is appropriate without being too thin or heavy.
Completeness4/5The tool surface covers core operations for RFC access: retrieving full documents, sections, and searching. A minor gap exists in lifecycle coverage, such as listing all RFCs or filtering by metadata, but agents can work around this with the provided tools.
Average 3/5 across 3 of 3 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
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This repository is licensed under Apache 2.0.
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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 states the action ('Get') but does not describe any behavioral traits such as whether this is a read-only operation, potential rate limits, error conditions, or the format of returned data. This is inadequate 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.
Conciseness5/5Is 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 and wastes no space, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given 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 incomplete. It does not address behavioral aspects like safety, performance, or return values, which are crucial for an agent to use the tool effectively. The description alone is insufficient for a tool with no structured data beyond the input schema.
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 input schema has 100% description coverage, clearly documenting both parameters ('number' and 'section'). The description adds no additional meaning beyond what the schema provides, such as examples of section formats or clarification on what constitutes a 'specific section'. With 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('a specific section from an RFC'), making the purpose understandable. However, it does not explicitly distinguish this tool from its sibling 'get_rfc' (which likely retrieves entire RFCs) or 'search_rfcs' (which likely searches across RFCs), missing an opportunity for full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 its siblings ('get_rfc' and 'search_rfcs'). It lacks any context about alternatives, prerequisites, or exclusions, leaving the agent to infer usage 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.
- 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 searches by keyword but doesn't describe how results are returned (e.g., format, sorting, pagination), whether it's read-only or has side effects, or any limitations like rate limits. This leaves significant gaps 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence: 'Search for RFCs by keyword'. It's front-loaded and wastes no words, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given 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 incomplete. It doesn't explain what the search returns (e.g., list of RFCs with metadata), how results are structured, or any behavioral traits like error handling. For a search tool with no structured output information, this leaves the agent guessing about the tool's full functionality.
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 description mentions searching 'by keyword', which aligns with the 'query' parameter in the schema. However, with 100% schema description coverage, the schema already documents both parameters ('query' and 'limit') clearly. The description adds minimal value beyond what the schema provides, meeting the baseline for high coverage.
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 tool's purpose: 'Search for RFCs by keyword'. It specifies the verb ('Search') and resource ('RFCs'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get_rfc' or 'get_rfc_section', which likely retrieve specific RFCs rather than searching across them.
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. It doesn't mention sibling tools like 'get_rfc' or 'get_rfc_section', nor does it specify any context or exclusions for usage. The agent must infer usage based on the name alone.
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 the basic action. It lacks details on behavioral traits such as error handling, rate limits, authentication needs, or what 'fetch' entails (e.g., network call, cached data). 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words, making it highly efficient and front-loaded. It directly communicates the core purpose without unnecessary elaboration.
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 2 parameters and no output schema, the description is minimally adequate but incomplete. It lacks context on usage guidelines and behavioral transparency, which are important given the absence of annotations and output schema, leaving room for improvement.
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?
Schema description coverage is 100%, so the schema fully documents both parameters. The description adds no additional meaning beyond implying the 'number' parameter is used for fetching, which aligns with the schema. 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch') and resource ('RFC document by its number'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_rfc_section' or 'search_rfcs', which prevents 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 Guidelines2/5Does 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 like 'get_rfc_section' or 'search_rfcs'. The description only states what it does, not when it's appropriate, leaving the agent without context for tool selection.
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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