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@marocain/mcp-server

@marocain/mcp-server

by Hei33enberg
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

gin_ask

Ask a natural-language question about Moroccan real estate and receive a cited, scored investment analysis grounded in property data and guides.

Instructions

Ask T{AI]GIN — the {GIN} agentic investment analyst — a one-shot natural-language question. It plans, searches the catalogue + authored guides, scores with the {GIN} pillars and answers grounded with citations. Use for open questions ('which Tangier district has the best rental upside?', 'why Morocco over Dubai?'). Never returns agent contact details.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "gin_ask"
  }
}

Input Schema

NameRequiredDescriptionDefault
qYesNatural-language question for the analyst.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.9

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses several behavioral traits: it is one-shot, plans, searches the catalogue and guides, scores with GIN pillars, and returns citations. It also states a clear negative behavior (does not return agent contact details). This is solid transparency, though it does not cover potential errors or edge cases.

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 compact (roughly 40 words) and front-loaded with the core action ('Ask...'). Every sentence contributes: it defines the resource, explains the process, gives usage direction with examples, and states a key limitation. No filler or redundancy.

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?

For a single-parameter tool with no annotations or output schema, the description is largely complete. It explains what the tool does, how it works, and what it returns (an answer with citations). The only minor gap is that it does not mention what happens if the question is out of scope or unanswerable, but this is acceptable for a natural-language interface.

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 only describes 'q' as a natural-language question. The description expands on this by specifying that questions should be open-ended and provides concrete examples, which helps an agent formulate appropriate queries. This adds meaningful semantics beyond the schema's basic description.

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 this tool asks a one-shot natural-language question to an investment analyst. It specifies the resource (T{AI]GIN) and the action (ask), and distinguishes itself by focusing on open questions rather than structured lookups. Examples of open questions make the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use for open questions' and provides two example questions, giving clear context for when to invoke this tool. It also mentions a limitation ('Never returns agent contact details'), but does not explicitly name alternative tools for non-open questions, which leaves a slight gap in guidance.

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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