outris-identity-mcp

Identity resolution MCP server for phone/email lookups across 31+ services. Global + India coverage.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
99%
Vollständigkeit des Schemas
100%
Qualität der Benennung
92%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Befunde (1)

  • LOWTool 'check_digital_commerce_activity' name length outside 3-30 rangein check_digital_commerce_activity

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~2,670Tokens (Tool-Definitionen)
~669 BTypische Antwortgröße
Erhebliche Auswirkung auf die Aufmerksamkeit (2.09% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "outris-identity-mcp": {
      "url": "https://mcp-server.outris.com/http"
    }
  }
}

Remote-Endpunkte

https://mcp-server.outris.com/httpstreamable-http

Was es kann

Tool-Inventar

Tools (19)

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⚪investigate_phone(phone, depth)

Investigate an Indian mobile number and return who is behind it — name(s), addresses, alternate phone numbers, and social/digital footprint. Use depth='basic' for a fast identity bundle (default) or depth='full' for a comprehensive multi-source investigation (slower). Best for: 'who owns this number', caller ID, KYC, skip-tracing. Cost: 3 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Indian mobile number (10-digit, with or without +91)."
    },
    "depth": {
      "type": "string",
      "enum": [
        "basic",
        "full"
      ],
      "description": "basic = fast identity bundle (default); full = comprehensive investigation (slower)."
    }
  },
  "required": [
    "phone"
  ]
}
🟡assess_fraud_risk(phone, detailed)

Assess the fraud risk of an Indian mobile number. Returns a composite risk profile: SIM age / age-on-network, number revocation status, SIM-swap / port signals, and digital & financial exposure. Set detailed=true for the full signal breakdown. Best for: onboarding risk checks, is-this-number-risky. Cost: 3 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Indian mobile number (10-digit, with or without +91)."
    },
    "detailed": {
      "type": "boolean",
      "description": "Include the full raw signal breakdown. Default false."
    }
  },
  "required": [
    "phone"
  ]
}
🟢find_contacts(phone, consent_token, consent)

Skip-trace an Indian mobile number for the person's ALTERNATE phone numbers and current, geocoded addresses. Requires the end user's consent: ask the user to open the consent link in portal.outris.com/mcp and pass the consent_token they receive. Best for: debt collection, locating a person. Never fabricate consent. Cost: 3 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Indian mobile number (10-digit, with or without +91)."
    },
    "consent_token": {
      "type": "string",
      "description": "Server-issued consent token from portal.outris.com/mcp (preferred)."
    },
    "consent": {
      "type": "string",
      "description": "Deprecated legacy consent flag ('Y'); accepted only during migration."
    }
  },
  "required": [
    "phone"
  ]
}
🟡due_diligence_person_start(phone, consent_token, consent, name, pan, ...)

Start a full due-diligence / background check on a PERSON, anchored on their mobile number (optionally add name, PAN, DOB, email, city). Covers PEP, sanctions, enforcement, cybercrime, breaches, directorships, and adverse media. PREMIUM and ASYNC (~40-70s): it returns a job_id — poll check_job until status is 'complete'. Requires consent: ask the user to open the consent link in portal.outris.com/mcp and pass the consent_token. Cost: 5 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Indian mobile number (10-digit, with or without +91)."
    },
    "consent_token": {
      "type": "string",
      "description": "Server-issued consent token (preferred)."
    },
    "consent": {
      "type": "string",
      "description": "Deprecated legacy consent flag ('Y'); migration only."
    },
    "name": {
      "type": "string",
      "description": "Optional subject full name."
    },
    "pan": {
      "type": "string",
      "description": "Optional PAN — strongest key for PEP/enforcement."
    },
    "dob": {
      "type": "string",
      "description": "Optional date of birth (disambiguates common names)."
    },
    "email": {
      "type": "string",
      "description": "Optional subject email."
    },
    "city": {
      "type": "string",
      "description": "Optional city (adverse-media disambiguation)."
    }
  },
  "required": [
    "phone"
  ]
}
🟢check_job(job_id)

Check the status/result of an async job by job_id (e.g. from due_diligence_person_start). Free to poll — wait ~10s between polls. Cost: 0 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "job_id": {
      "type": "string",
      "description": "The job_id returned by an async tool."
    }
  },
  "required": [
    "job_id"
  ]
}
⚪investigate_email(email)

Trace the person behind an email address — linked names, phone numbers, addresses, and known data breaches. Best for: reverse email lookup, digital footprint, cross-referencing an identity. Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "email": {
      "type": "string",
      "description": "Email address to investigate."
    }
  },
  "required": [
    "email"
  ]
}
⚪resolve_company(company_name)

Resolve an Indian company from its NAME and return its CIN (Corporate Identification Number) plus any GSTIN / MSME registrations discovered along the way. Best for: 'is this a real company', KYB entry point, finding a CIN from a company name. Cost: 3 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "company_name": {
      "type": "string",
      "description": "Company name to resolve."
    }
  },
  "required": [
    "company_name"
  ]
}
⚪lookup_gst(gstin)

Look up GST registration details for a business by its GSTIN (15-character GST number). Returns legal/trade name, status, registration type, and address. Best for: GST verification, vendor onboarding. Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "gstin": {
      "type": "string",
      "description": "15-character GSTIN."
    }
  },
  "required": [
    "gstin"
  ]
}
⚪verify_pan(pan)

Verify an Indian PAN (Permanent Account Number) and return the holder's name, status, and PAN type (individual / company / etc.). Best for: KYC, PAN validity checks. Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "pan": {
      "type": "string",
      "description": "10-character PAN (e.g. ABCDE1234F)."
    }
  },
  "required": [
    "pan"
  ]
}
⚪lookup_vehicle(rc_number)

Look up an Indian vehicle by its RC (registration) number — returns make/model, registration details, and the registered owner. Best for: vehicle verification, RC checks. Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "rc_number": {
      "type": "string",
      "description": "Vehicle registration number (e.g. MH12AB1234)."
    }
  },
  "required": [
    "rc_number"
  ]
}
⚪verify_bank_account(account_number, ifsc)

Validate an Indian bank account WITHOUT moving any money (no-debit NPCI validation) and return whether it is valid plus the account holder's name for matching. Best for: payout/beneficiary verification. This does NOT transfer funds. Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "account_number": {
      "type": "string",
      "description": "Bank account number to validate."
    },
    "ifsc": {
      "type": "string",
      "description": "IFSC code of the account's branch."
    }
  },
  "required": [
    "account_number",
    "ifsc"
  ]
}
⚪smart_lookup(question, identifiers, consent_token, consent)

Answer any other identity / KYC / business question when no specific tool fits. Provide a natural-language `question` plus the `identifiers` you already have (phone, email, PAN, GSTIN, CIN, DIN, UAN, IFSC, vehicle RC, UPI VPA, UDIN, or a company name). It figures out the right lookup — or a short sequence — and returns the answer. Only pass identifiers the user actually gave you; never invent one. For consent-required lookups, ask the user to open the consent link in portal.outris.com/mcp and pass the consent_token they receive. Cost: 3 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "question": {
      "type": "string",
      "description": "The user's question in plain language."
    },
    "identifiers": {
      "type": "object",
      "description": "Identifiers you have, as {type: value} — e.g. {\"pan\": \"ABCDE1234F\"} or {\"phone\": \"9876543210\"}. Only include values the user provided."
    },
    "consent_token": {
      "type": "string",
      "description": "Server-issued consent token from portal.outris.com/mcp (preferred for consent-required lookups)."
    },
    "consent": {
      "type": "string",
      "description": "Deprecated legacy consent flag ('Y'); accepted only during migration. Prefer consent_token."
    }
  },
  "required": [
    "question",
    "identifiers"
  ]
}
🟢check_online_platforms(phone)

**What it does:** Checks if a phone number is registered on major global platforms (Amazon, Instagram, Snapchat). **Input:** Phone number (with or without country code). **Returns:** Registration status (true/false) for each specific platform. **Best for:** Digital footprint analysis, verifying if a number is "real" and active on social/shopping apps. Cost: 1 credit

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Phone number (with or without country code)"
    }
  },
  "required": [
    "phone"
  ]
}
🟢get_identity_profile(phone)

**What it does:** Comprehensive identity report. Fetches names, emails, addresses, metadata, and risk scores in one go . **Input:** Phone number. **Returns:** Complete JSON profile containing all linked entities. **Best for:** Deep investigations where you need the "full picture" immediately. Understand if similar names, addresses appear, then that gives more confidence Cost: 3 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Phone number"
    }
  },
  "required": [
    "phone"
  ]
}
🟢get_name(phone)

**What it does:** identifying the owner name of a phone number. **Input:** Phone number (with or without country code). **Returns:** List of full names linked to this phone with confidence scores. **Best for:** KYC verification, caller ID, finding out "who called me". Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Phone number"
    }
  },
  "required": [
    "phone"
  ]
}
🟢get_email(phone)

**What it does:** Finds email addresses linked to a phone number. **Input:** Phone number. **Returns:** List of email addresses with confidence scores. **Best for:** Digital footprint analysis, finding contact details, or cross-referencing identities. Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Phone number"
    }
  },
  "required": [
    "phone"
  ]
}
🟢get_address(phone)

**What it does:** Finds physical addresses associated with a phone number. **Input:** Phone number. **Returns:** List of addresses with metadata (e.g., "shipping", "billing", "home") and dates. **Best for:** Fraud investigation, delivery verification, and location analysis. Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Phone number"
    }
  },
  "required": [
    "phone"
  ]
}
🟢get_alternate_phones(phone)

Get other phone numbers belonging to the same person. Returns: List of alternate phone numbers linked through shared identities (same name, email, or address). Use when: User wants to find all phones associated with a person. Example queries: - "What other phones does this person have?" - "Find alternate numbers for 9876543210" - "Are there other phones linked to this one?" Cost: 2 credits

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Phone number"
    }
  },
  "required": [
    "phone"
  ]
}
🟡check_digital_commerce_activity(phone, include_demographics)

**What it does:** Checks if a phone number has been used for any digital commerce activity (ecommerce, travel, quick-commerce). **Input:** Phone number (Indian numbers only, add ISD code infront). **Returns:** Boolean flags for overall commerce types, activity timeline, and demographics if available. **Best for:** Assessing if a phone number belongs to a real, active consumer vs. a throwaway number. Cost: 1 credit

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "phone": {
      "type": "string",
      "description": "Phone number (with or without country code)"
    },
    "include_demographics": {
      "type": "boolean",
      "description": "Include age/gender estimation (default: true)"
    }
  },
  "required": [
    "phone"
  ]
}

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