Recherche et lecture des guides de connexion de moncompte.org (MCP, lecture seule).
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Usage analytics
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Average 4.2/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: search_articles finds articles by keywords, and get_article retrieves a specific article by slug. There is no overlap in functionality.
Both tools follow a consistent verb_noun pattern (search_articles, get_article), making the naming predictable and readable.
With only 2 tools, the server is slightly under the typical 3-15 range, but it covers the essential operations of searching and retrieving articles for this narrow domain, so it earns its place.
The tool set covers the core workflow of finding and viewing articles. A minor gap could be the lack of a 'list all articles' function, but search with keywords can suffice, so completeness is good.
get_articleAInspectRetourne le contenu complet d'une notice de moncompte.org à partir de son slug (obtenu via search_articles).
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Slug de l'article (ex. « mon-compte-revolut »). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It indicates the tool returns the full content, but does not disclose error handling, read-only nature, or performance. For a simple retrieval, it is adequate but could add more.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is concise and front-loaded with the purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (1 parameter, no output schema), the description adequately states what the tool does and where the input comes from. It lacks mention of error scenarios but is generally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds value by explaining that the slug comes from search_articles, providing context beyond the schema's parameter description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('retourne'), the resource ('contenu complet d'une notice'), and the input ('slug'). It also distinguishes from the sibling tool 'search_articles' by specifying that the slug is obtained via it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states that the slug should be obtained via search_articles, providing clear context for when to use this tool. It does not explicitly state when not to use, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_articlesAInspectRecherche des notices/guides « mon compte » de moncompte.org par mots-clés. Retourne une liste (titre, slug, URL, description). Utiliser le slug avec get_article.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Nombre de résultats (1-20, défaut 10). | |
| query | Yes | Mots-clés de recherche (ex. « se connecter Revolut »). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes the return format (list of fields) and gives an example query. However, it lacks details on ordering, pagination, or search behavior (fuzzy matching, operators). Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences front-loading the purpose and return format, then linking to sibling tool. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (two parameters, no output schema), the description fully covers what an agent needs: what it does, what it returns, and how to chain with get_article. The example in the schema adds further clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters, including an example for query. The description does not add additional meaning beyond what the schema already provides, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches for notices/guides by keywords, returns a list with title, slug, URL, description, and instructs to use the slug with get_article, distinguishing it from the sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says to use the slug with get_article, providing clear guidance on when to use this tool versus the sibling. No explicit when-not-to-use, but the context is clear.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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