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MeruLocal

raivatedu-mcp-server

by MeruLocal

Get RaivatEdu Contact Information

raivatedu_get_contact_information
Read-onlyIdempotent

Retrieve RaivatEdu's published sales, support, and security email addresses plus contact and demo page URLs by market, without submitting forms or sending messages.

Instructions

Retrieve RaivatEdu's publicly listed contact details: sales, support and security email addresses plus the contact and demo page URLs.

Email addresses come from the Organization JSON-LD contact points (the site's own machine-readable contact data). This tool does NOT submit forms or send messages — it only reads published contact details.

Args:

  • market (optional): locale used for the contact/demo page URLs (in, us, gb, ca, au, nz, ie, sg, ae, za); defaults to the configured market.

  • response_format ('markdown' | 'json'): output format (default markdown).

Returns JSON shape: { "general_email": string | null, "contact_points": [ { "type": string, "email": string | null, "telephone": string | null } ], "contact_page": string, "demo_page": string }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoMarket/locale segment. One of: in, us, gb, ca, au, nz, ie, sg, ae, za. Defaults to the server's configured market (initially 'in' for India).
response_formatNoOutput format: 'markdown' for a human-readable summary (default) or 'json' for the full structured object.markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so the safety profile is covered; the description adds real value by disclosing the data provenance (Organization JSON-LD contact points) and reiterating that no messages are sent. It does not discuss caching, freshness, or failure behavior when a contact point is absent, keeping it below a 5.

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?

Purpose and the key negative constraint are front-loaded in the first two sentences, with details following in a scannable Args/Returns layout. The Returns JSON block is somewhat verbose but compensates for the absence of an output schema, so it largely earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description supplies the full return shape including nullable fields, and the only two parameters are fully documented. A caller has everything needed to invoke it correctly and interpret the response.

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% and both parameters already carry enum lists and default explanations in the schema. The description restates the market options and the response_format default without adding syntax or semantics beyond the structured fields, so baseline 3 applies.

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?

States a specific verb and resource ('Retrieve RaivatEdu's publicly listed contact details') and enumerates exactly what is returned (sales, support, security emails plus contact/demo URLs). This is clearly distinguishable from siblings like get_website_info or list_pages without opening either schema.

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?

Gives a clear context for use (reading published contact data) and an explicit when-not ('does NOT submit forms or send messages'), which prevents a plausible misuse. It does not name a sibling alternative for related lookups such as get_website_info, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.