Le Parrain MCP
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct action: retrieving program details, searching blog articles, searching programs, and suggesting missing programs. There is no overlap or ambiguity.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern in snake_case (get_program, search_blog, search_programs, suggest_program), making them predictable and easy to distinguish.
Tool Count5/5With 4 tools, the set is tightly scoped to the core functionality of a referral program directory: discovering, detailing, and suggesting programs, plus supporting blog content. No tool feels extraneous or missing.
Completeness4/5The set covers the main use cases: program search, detail retrieval, blog advice, and program suggestions. Lacks explicit update or delete actions, but those may be out of scope for a directory service.
Average 3.9/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 29 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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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, the description adds some behavioral context by stating the link is 'résolu pour vous' (resolved). However, it does not disclose other traits like read-only nature, side effects, or error conditions.
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?
A single, concise sentence that front-loads the core purpose. Every word adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 param, no output schema), the description covers the main functionality and return content. It lacks details about response format or structure, but overall is adequate.
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 coverage is 100% and the schema description already explains the slug parameter thoroughly. The tool description adds no further parameter meaning beyond what the schema provides, staying at baseline for high coverage.
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 the tool returns details of a referral program (description + resolved referral link), using a specific verb ('Renvoie') and resource. It distinguishes from siblings such as search_programs and suggest_program.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The slug parameter hints at using search_programs to get the slug, but no direct advice on selecting this tool over alternatives.
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 must disclose behavioral traits. It only states the action (search) and outcome (returns programs) without mentioning read-only nature, limitations, or side effects. Minimal behavioral disclosure.
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?
Two sentences, front-loaded with purpose, followed by usage hint. Every sentence earns its place; no unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one param, no output schema), the description covers essential context: what it searches, what it returns, and when to use it. Could be improved by mentioning output format or pagination, but sufficient for basic understanding.
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% for the single parameter. The tool description adds no new details about the parameter beyond the schema description, so it does not exceed the baseline 3.
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 searches blog articles and returns related programs. It differentiates from siblings (get_program, search_programs, suggest_program) by specifying the blog resource and broader query applicability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'Utile pour des questions plus larges qu'une simple recherche de programme,' which implicitly guides when to use this tool vs. a program-specific search. It provides clear context but lacks explicit 'when-not-to-use' statements.
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, the description bears full burden. It discloses the key behavior of returning a personalized link based on user login and publication status. However, it omits other traits like pagination, error handling, or authentication requirements.
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?
Two concise sentences, front-loaded with the action verb 'Cherche' and clearly structured. Every sentence adds essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with one parameter and no output schema, the description is fairly complete. It covers the core functionality and the unique link behavior. Could mention result format or edge cases, but not critical.
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 coverage is 100% for the single parameter 'query', which already has a description. The tool description adds no additional semantic detail beyond restating the keyword concept, so it adds minimal value.
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 the tool searches for sponsorship programs in a specific directory and returns results with personalized links. This distinguishes it from siblings like get_program (single program) and search_blog (blog search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for finding sponsorship programs but does not explicitly state when to use this tool over alternatives like suggest_program or when not to use it. No exclusions or context for alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the burden of disclosing behavior. It informs that the proposal goes through human moderation before any publication and that automatic online posting does not occur. This is important for an agent to set expectations, though more detail on the moderation process or timing could be added.
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. It front-loads the purpose and immediately follows with the key behavioral note about moderation. No unnecessary words or repetition.
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?
Given the tool has 3 parameters, no output schema, and no annotations, the description provides the core purpose and a key behavior (moderation). However, it lacks information about what the agent should expect as a return value (e.g., confirmation, ID) or what happens after successful suggestion. This leaves a slight gap in completeness.
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?
All three parameters (name, url, category) are described in the schema with 100% coverage. The description does not add additional semantic meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 the tool's purpose: to propose a sponsorship program not already in the directory. The verb 'Propose' and resource 'programme de parrainage absent de l'annuaire' are specific. Siblings like get_program, search_blog, and search_programs are clearly distinct (retrieval/search vs. suggesting new).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for suggesting a program that is absent from the directory, giving clear context for use. However, it does not explicitly state when NOT to use it or suggest alternatives, though the sibling tools are quite different in nature.
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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