DelphaMCP by Delpha-Assistant - MCP Server

Delpha Data Quality MCP

Intelligent AI Agents to ensure accurate, unique, and reliable customer data

📋 Table of Contents

🌟 Overview
🎬 Demo
🚀 Quickstart
🗝️ Getting Client Credentials
🛠️ Tools
📞 Support

🌟 Overview

Delpha is an AI-driven data quality solution that uses intelligent AI Agents to ensure accurate, unique, and reliable customer data. Delpha's specialized AI Agents automate data cleansing and enrichment, helping businesses enhance operational efficiency and drive stronger revenue performance.

Reduce Data Maintenance Costs: Delpha minimizes the need for manual data cleanup, reducing labor costs and overhead associated with constant data maintenance.
Improve Sales Productivity: By automating data quality tasks, Delpha frees up significant portions of sales teams' schedules, allowing them to focus on selling rather than data entry and correction.
Shorten Data Migration: Delpha accelerates the process of unifying CRM datasets, enabling sales reps to confidently approach newly acquired customers and drive incremental revenue sooner.
Deduplication with AI: Delpha's advanced AI accurately scores potential duplicates by analyzing multiple fields and detecting subtle variations, offering both automatic and manual merging options.

🎬 Demo

See Delpha MCP in action—validate and enrich data directly from your AI assistant.

🚀 Quickstart

Install the package
```
pip install delpha-mcp
```

Configure Add this to your MCP settings (replace env values with your credentials):

{
  "mcpServers": {
    "Delpha": {
      "command": "python",
      "args": ["-m", "delpha_mcp"],
      "env": {
        "DELPHA_CLIENT_ID": "your_client_id_here",
        "DELPHA_CLIENT_SECRET": "your_client_secret_here"
      }
    }
  }
}

Restart your app — Delpha tools are now available.

🗝️ Getting Client Credentials

Delpha MCP uses OAuth2. Please contact support.api@delpha.io to request your client ID and secret.

🛠️ Tools

Delpha MCP exposes a set of intelligent tools to assess and improve the quality of your data. Each tool is designed to address specific data quality challenges, providing actionable insights and suggestions for improvement.

Email

MCP Tool Names

findAndValidateEmail
getEmailResult

What it does Keep email data deliverable and up-to-date by discovering missing addresses and validating existing ones.

How we assess

Completeness: Find and populate missing addresses.
Validity: Check syntax and deliverability signals.
Accuracy: Ensure the email fits the intended person/entity context.
Consistency: Align inputs with normalized output.

Extras

Classification (e.g., professional vs. personal) to support compliant outreach.
AI recommendations with confidence scores when a better email is likely.

Address

MCP Tool Names

findAndValidateAddress
getAddressResult

What it does Standardize, validate, and complete postal addresses to improve delivery, analytics, and territory planning.

How we assess

Completeness: Fill missing elements (street no., street, city, postal code, country).
Validity: Conformity to country-specific postal rules and canonical formats.
Accuracy: Normalize structure and resolve ambiguities.
Consistency: Compare input vs. normalized output.

Extras

Returns a normalized, well-structured address.
AI recommendations with confidence scores when multiple plausible addresses exist.

Website

MCP Tool Names

findAndValidateWebsite
getWebsiteResult

What it does Normalize and canonicalize company websites (domain, scheme, redirects) and suggest likely sites when the input is missing or off.

How we assess

Completeness: Populate missing websites/root domains.
Validity: Confirm proper URL formatting and safe normalization (scheme, subdomain, trailing slash, redirects).
Accuracy: Check that the URL matches the intended entity.
Consistency: Compare input vs. normalized/canonical URL.

Extras

Returns the normalized (and redirected if applicable) URL.
AI recommendations with confidence scores.

MCP Tool Names

findAndValidateLinkedin
getLinkedinResult

What it does Normalize LinkedIn profile/company URLs and, when needed, suggest the most relevant pages using context like name, company, and website.

How we assess

Completeness: Detect presence/absence of a LinkedIn URL.
Validity: Validate format (e.g., /in/ for people, company page patterns); not a live profile/existence check.
Accuracy: Check that the URL aligns with provided context (first/last name, company name, website).
Consistency: Compare input vs. normalized URL.

Extras

Recommendations include URL, confidence, and helpful metadata (e.g., profile/page name, title/description, location, rank) to speed selection.

Phone

MCP Tool Names

findAndValidatePhone
getPhoneResult

What it does Normalize phone numbers to international standards and check basic plausibility.

How we assess

Completeness: Is a value present.
Validity: Does the number conform to country/region rules and basic plausibility checks (e.g., non-blacklisted patterns).
Consistency: Compare input vs. normalized E.164 output.

Notes

No accuracy score or side-field recommendations.
If no country is provided, inference follows a configured country preference order.

Name

MCP Tool Names

findAndValidateName
getNameResult

What it does Normalize person names and detect common data-entry issues to keep contact data clean.

How we assess

Completeness: Separate scoring for FirstName and LastName.
Validity: Check both parts against reference databases.
Consistency: Compare input vs. normalized casing, hyphenation, etc.
Misspelled: Flag likely typos and propose close alternatives.
Reversed: Detect when first and last names appear swapped.

Extras

Suggestions include corrected spelling, swapped order when appropriate, or simply the normalized version when everything looks good.
No accuracy score for names.

Legal ID

MCP Tool Names

findAndValidateLegalID
getLegalIDResult

What it does Validate, normalize, and enrich company legal identifiers across supported countries and ID types.

How we assess

Completeness: Determine ID type from provided country or input; populate when possible.
Validity: Normalize to canonical representation and verify against supported country rules and reference datasets.
Accuracy: Check that the ID corresponds to the intended entity using side fields (e.g., company name, address, website).
Consistency: Compare input vs. normalized value.

Extras

Returns enriched context for matched entities (e.g., company name, website, address, industry) and ranked recommendations when input and side fields point to multiple candidates.

The list of supported countries and ID types is maintained in Delpha’s documentation; implementations should rely on what’s enabled in your environment.

Email Insights

MCP Tool Name

getEmailInsights

What it does Extract structured signals from email bodies to update/contact records faster.

Examples of extracted fields

Name, phone(s), title, company, department, address
Social links
Out-of-office window
Confidence score

LinkedIn Import

MCP Tool Names

submitLinkedinImport
getLinkedinImportResult

What it does High-throughput importer for LinkedIn / Sales Navigator searches and lists. Submit a source URL and receive normalized profiles or companies at scale.

Flow

Start a job with submitLinkedinImport.
We handle throttling and retries.
Poll with getLinkedinImportResult for the final dataset URL.

Refer to the OpenAPI schemas for the exact input fields and outputs supported in your environment.

📞 Support

If you encounter any issues or have questions, please reach out to the Delpha team at support.api@delpha.io or open an issue in the repository.