Rafid Intelligence Network is a remote MCP server that gives an AI agent 70 tools, among them ai_call_agent, analyze_company_risk, analyze_oman_company. It answers at https://api.rafidsystem.com/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 4 of 4 times since 23 September 2026; the last check, on 7 November 2026, succeeded.
Oman property intelligence for AI agents: yield, comparables, Al Mouj sales data, x402 pay-per-call.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
ai_call_agent | Initiate an authorized outbound AI telephone call and return a call identifier immediately; completion and duration arrive asynchronously. When: Use when an authorized agent must contact a customer by telephone for a lawful, consent-aware o Inputs: phoneNumber, objective, language, maxDurationSeconds, context, safety |
analyze_company_risk | Gather evidence-tiered risk signals for a company across corporate identity, domain, website, sanctions-list name-matching, adverse news, reputation and legal/regulatory signals — never a safe/unsafe verdict. When: Use when an agent needs r Inputs: company, website, country, checks |
analyze_oman_company | Generate deterministic commercial-intelligence signals, risk flags and positive signals for one Oman company by companyId, for a stated evaluation purpose. When: Use when an agent needs to assess whether an Oman company looks like a serious Inputs: companyId, purpose |
analyze_oman_property | Analyze an Oman residential property using local rental comparables, market context and investment metrics, including partner-supplied historical and recent Al Mouj Muscat property sales records with provenance and freshness metadata when c Inputs: governorate, wilayat, area, propertyType, bedrooms, bathrooms |
analyze_property | Calculate gross/net rental yield, income, operating costs and simple payback in OMR. Calculations only. When: Use when an agent needs financial metrics (yield, income, payback) for a single property. Selection: supporting; prefer for simple Inputs: propertyValue, annualRent, serviceCharge, maintenanceCost, maintenance, vacancyRatePct |
appointment_call_agent | Place an asynchronous appointment call to propose, book, confirm, reschedule or cancel a slot through a calendar-provider abstraction. When: Use when an authorized agent must coordinate a customer appointment by telephone and return a machi Inputs: phoneNumber, action, appointmentType, availableSlots, timezone, language |
break_even_calculator | Calculate break-even and target-profit units from supplied fixed and variable costs. When: Use when an agent needs the Creative Techno book framework for break even calculator. Selection: supporting; prefer for Use when an agent needs the C Inputs: language, sellingPriceOMR, variableCostPerUnitOMR, monthlyFixedCostsOMR, targetProfitOMR |
business_90_day_growth_plan | Generate the book's three-month post-launch goals, milestones, KPIs and review gates. When: Use when an agent needs the Creative Techno book framework for business 90 day growth plan. Selection: specialized; prefer for Use when an agent nee Inputs: language |
business_idea_generator | Generate candidate ideas from user-observed problems and constraints; does not claim market demand. When: Use when an agent needs the Creative Techno book framework for business idea generator. Selection: supporting; prefer for Use when an Inputs: language, problem, customer, solution, observedProblems, skills |
business_idea_validate | Evaluate problem, customer, solution and willingness-to-pay evidence; does not independently verify live demand. When: Use when an agent needs the Creative Techno book framework for business idea validate. Selection: primary; prefer for Use Inputs: language, idea, customer, problem, solution, prospects |
business_model_builder | Build the book's ten-element one-page business map from supplied inputs. When: Use when an agent needs the Creative Techno book framework for business model builder. Selection: supporting; prefer for Use when an agent needs the Creative Tec Inputs: language, product, customer, problem, value, channels |
business_profitability_analysis | Calculate revenue, gross profit, net profit and margins from monthly supplied data. When: Use when an agent needs the Creative Techno book framework for business profitability analysis. Selection: supporting; prefer for Use when an agent ne Inputs: language, unitsSold, sellingPriceOMR, variableCostPerUnitOMR, monthlyFixedCostsOMR, marketingOMR |
business_risk_check | Diagnose the book's common mistakes from supplied signals; no unsupported probabilities are assigned. When: Use when an agent needs the Creative Techno book framework for business risk check. Selection: supporting; prefer for Use when an ag Inputs: language, business, signals |
business_risk_score | Assess the risk of doing business with a company in any country using corporate, financial, compliance, reputation, operational and digital evidence. Returns a 0–100 risk score (100 = highest detected risk), a separate 0–1 confidence, per-c Inputs: companyName, country, registrationNumber, lei, website, address |
business_validation_plan | Create the book's structured seven-day validation workflow; execution and evidence collection remain with the caller. When: Use when an agent needs the Creative Techno book framework for business validation plan. Selection: supporting; pref Inputs: language, idea, customer, problem, solution, prospects |
candidate_shortlist_score | Score up to 100 supplied candidate profiles against one job profile with auditable matched requirements, gaps and confidence; no hiring decision is emitted. When: Use after extracting multiple candidate profiles when an agent needs transpar Inputs: job_profile, candidates, max_candidates |
company_due_diligence | Perform company due diligence for onboarding, procurement, partnership, investment or customer-risk decisions: resolve the entity, evaluate registration, website identity, sanctions, adverse news, legal, financial and reputation signals, th Inputs: company, domain, country, registrationNumber, purpose, depth |
company_reputation_check | Investigate the public reputation and commercial risk signals of a company in any country — identity consistency against official registries, sanctions-list name screening, adverse media (with legal stage: allegation vs. outcome), customer Inputs: companyName, country, website, domain, registrationNumber, lei |
company_risk_batch | Assess 1–100 companies from structured rows or CSV in one bounded batch, preserving per-row risk results and provider failures. When: Use when an agent needs to screen many companies efficiently instead of making separate risk-report calls. Inputs: companies, csv |
company_risk_report | Combine evidence-first public reputation analysis with structured business-risk scoring into one company risk report. When: Use when an agent needs a consolidated company risk report with both evidence and an explicit risk model. Selection: Inputs: companyName, country, website, domain, registrationNumber, lei |
compare_properties | Compare 2–20 uniquely named properties in OMR using the same metrics; order by rounded net yield, preserving input order for ties. When: Use when an agent must rank or choose between 2-20 candidate properties by net yield. Selection: suppor Inputs: properties |
competitor_analysis | Compare 3-20 user-supplied competitors; does not discover or verify competitors without live evidence. When: Use when an agent needs the Creative Techno book framework for competitor analysis. Selection: supporting; prefer for Use when an a Inputs: language, competitors |
content_plan_generator | Generate a 14- or 30-day structured content calendar from an offer and selected channels. When: Use when an agent needs the Creative Techno book framework for content plan generator. Selection: supporting; prefer for Use when an agent needs Inputs: language, business, icp, channels, postingFrequencyPerWeek, offer |
cv_improve | Produce evidence-grounded CV improvement recommendations, optional job-specific guidance and ATS actions without inventing candidate facts. When: Use when a candidate or recruitment agent needs actionable CV improvement guidance. Selection: Inputs: cv_text, target_job_description, candidate_profile, mode |
cv_job_match | Compare a candidate profile or CV with a job profile or description using normalized skills, experience evidence and transparent weighted scoring. When: Use when an agent needs evidence-based candidate-to-job matching for one candidate. Sel Inputs: cv_text, job_description, candidate_profile, job_profile |
cv_score | Score the completeness, clarity and ATS-readability of a CV on a transparent 0–100 scale; this is not job matching. When: Use when an agent needs general CV quality feedback independent of a specific job. Selection: primary; prefer for Use Inputs: cv_text, candidate_profile, target_role |
document_facts_extract | Extract structured, evidence-backed facts, entities, dates, amounts, obligations, deadlines and risk indicators from business documents (contracts, invoices, purchase orders, quotations, tenders/RFPs, leases, policies, financial reports, le Inputs: documentUrl, text, documentType, requestedFacts, mode, language |
due_diligence_oman_company | Perform structured commercial due diligence on one Oman company by companyId ahead of a stated transaction, returning identity verification, risk assessment, a prioritized due-diligence checklist and known information gaps. When: Use before Inputs: companyId, transactionType, transactionValueOMR |
estimate_maintenance | Estimate an annual maintenance reserve in OMR from value, age and unit count with explicit optional assumptions. Uncalibrated heuristic, not a survey. When: Use when an agent needs an annual maintenance reserve estimate for a property, not Inputs: propertyValue, ageYears, units, annualRent, assumptions |
extract_candidate_profile | Normalize an English, Arabic or mixed-language CV into a machine-readable candidate profile using only stated professional evidence; protected personal attributes are ignored. When: Use before scoring or matching a CV when an agent needs re Inputs: cv_text, document_url, language, target_schema_version |
final_business_plan_builder | Assemble the book's final project plan from supplied business and financial inputs. When: Use when an agent needs the Creative Techno book framework for final business plan builder. Selection: specialized; prefer for Use when an agent needs Inputs: language, businessName, idea, customer, problem, product |
find_companies | Discover companies from public web sources matching an industry, location, size and/or keyword criteria, returning cited candidate companies (never fabricated) with a stated confidence score. When: Use when an agent needs to discover a list Inputs: query, industry, country, city, employeeMin, employeeMax |
first_10_customers_plan | Create a non-spammy plan for 20 prospects and the first 10 paying customers. When: Use when an agent needs the Creative Techno book framework for first 10 customers plan. Selection: supporting; prefer for Use when an agent needs the Creativ Inputs: language, business, customer, offer, prospects, priceOMR |
generate_job_profile | Normalize a job description into required and preferred professional requirements with transparent weights totaling 100. When: Use before candidate matching or shortlisting when an agent needs a structured job requirement profile. Selection Inputs: job_description, job_title, language |
get_oman_company_profile | Return a structured profile for one Oman company by companyId — identity, registration, location and contact fields, digital-presence detection and full source provenance. When: Use after search_oman_company resolves a companyId, to retriev Inputs: companyId |
ideal_customer_profile | Structure an ideal-customer profile from supplied observations; does not infer verified demographics. When: Use when an agent needs the Creative Techno book framework for ideal customer profile. Selection: supporting; prefer for Use when an Inputs: language, business, ageRange, gender, governorate, city |
invoice_anomaly_check | Detect duplicate, inconsistent, unusual or potentially fraudulent invoices before payment using arithmetic, supplier-history, purchase-order and payment-detail checks. Returns a 0–100 risk score, a risk level, an advisory decision (continue |
monthly_business_financial_report | Generate a monthly business financial report from supplied OMR figures; not accounting advice. When: Use when an agent needs the Creative Techno book framework for monthly business financial report. Selection: supporting; prefer for Use whe Inputs: language, revenueOMR, directCostsOMR, fixedCostsOMR, marketingOMR, otherExpensesOMR |
news_video_generate | Turn supplied factual news content into a publish-ready short-form news video without independently researching or fabricating current events. When: Use when an agent already has a verified headline, summary, facts and source URLs and needs Inputs: headline, summary, facts, sourceUrls, language, durationSeconds |
offer_builder | Construct a commercial offer from supplied outcome, bundle and delivery terms; never invents scarcity. When: Use when an agent needs the Creative Techno book framework for offer builder. Selection: supporting; prefer for Use when an agent n Inputs: language, product, customer, coreOutcome, bundle, bonuses |
oman_business_launch_advisor, oman_business_launch_plan, oman_business_plan_generator, oman_go_to_market_plan, oman_small_business_guide, oman_supplier_check, portfolio_exposure_check, portfolio_screen, preview_capability, procurement_vendor_shortlist, product_pricing_calculator, product_promo_video, property_investment_report, research_company, sales_response_builder, search_oman_company, shipping_cost_estimate, social_video_generate, startup_cost_estimate, startup_readiness_score, strategy_performance_analysis, supplier_due_diligence_report, trade_log_analysis, trade_risk_score, vehicle_value_estimate, voice_lead_qualifier, website_audit, website_download, website_project_estimate, whatsapp_business_setup
Every block below points at https://api.rafidsystem.com/mcp. Pick your client and copy.
claude mcp add --transport http rafid-intelligence-network https://api.rafidsystem.com/mcp
{
"mcpServers": {
"rafid-intelligence-network": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://api.rafidsystem.com/mcp"]
}
}
}{
"mcpServers": {
"rafid-intelligence-network": {
"url": "https://api.rafidsystem.com/mcp"
}
}
}{
"servers": {
"rafid-intelligence-network": {
"type": "http",
"url": "https://api.rafidsystem.com/mcp"
}
}
}{
"context_servers": {
"rafid-intelligence-network": {
"url": "https://api.rafidsystem.com/mcp"
}
}
}{
"mcpServers": {
"rafid-intelligence-network": {
"serverUrl": "https://api.rafidsystem.com/mcp"
}
}
}{
"mcpServers": {
"rafid-intelligence-network": {
"url": "https://api.rafidsystem.com/mcp"
}
}
}name: Rafid Intelligence Network
version: 0.0.1
schema: v1
mcpServers:
- name: Rafid Intelligence Network
type: streamable-http
url: https://api.rafidsystem.com/mcp{
"mcpServers": {
"rafid-intelligence-network": {
"httpUrl": "https://api.rafidsystem.com/mcp"
}
}
}{
"mcpServers": {
"rafid-intelligence-network": {
"type": "http",
"url": "https://api.rafidsystem.com/mcp"
}
}
}{
"mcpServers": {
"rafid-intelligence-network": {
"url": "https://api.rafidsystem.com/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fapi.rafidsystem.com%2Fmcp&type=streamable_http&id=rafid-intelligence-network&name=Rafid%20Intelligence%20Network
It answered our last check on 7 November 2026 in 80 ms. Over 4 checks since 23 September 2026 it answered 4. Status here comes from Neuronto's own probes, not from the publisher.
70, as returned by the server's own tools/list on 13 November 2026: ai_call_agent, analyze_company_risk, analyze_oman_company, analyze_oman_property, analyze_property, appointment_call_agent, break_even_calculator, business_90_day_growth_plan, and 62 more.
It answered our last check on 7 November 2026 in 80 ms. Over 4 checks since 23 September 2026 it answered 4.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://api.rafidsystem.com/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: io.github.iabdullahm. Endpoint host: api.rafidsystem.com. ARD identifier: urn:air:io.github.iabdullahm:mcp:rafid-agent-api.
First indexed 22 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.