"DNS Doctor" matching MCP servers:

A stdio MCP server exposing a validate_emails tool that lets agents screen email lists without sending mail or probing SMTP, checking syntax, DNS/MX records, disposable domains, role accounts, free providers, typo suggestions, and SPF/DMARC. Each address comes back with a valid/risky/invalid/unknown verdict plus machine-readable reason codes so agents can clean leads and signups before outreach or import.

MCP server for DTS Engine 6.1 that enables agents to create, validate, and run 3D digital-twin tile publishing pipelines from shapefiles, photogrammetry, DEM/DOM, BIM, and point clouds, with tools for pipeline introspection, error resolution, and OSGB publishing.

Enables coding agents to diagnose root causes of AWS Glue, MWAA (Airflow), Athena and Lake Formation failures, either from an error/log incident or from live read-only lookups of a Glue job run, MWAA environment or Athena query. Exposes tools that return ranked candidate causes with evidence, fix steps and documentation links, plus a listing of the supported failure patterns.

DATPAQ exposes 34 production data & utility APIs — IP geolocation, DNS/WHOIS/MX lookups, email & phone validation, currency & precious-metals rates, aircraft/VIN lookups, web scraping & screenshots, and more — through one hosted, streamable-HTTP MCP endpoint.

Enables operating Dataiku DSS projects, datasets, and Agent tools from any MCP client over Streamable HTTP, with read-only by default and secure bearer-token authentication.

Enables agents to diff inventory snapshots from CSV files or live Shopify stores, surfacing SKU mismatches, oversell risks, blank-vs-zero issues, barcode conflicts, and sync health, with data processed locally.

MCP server for verifying B2B contact records via email syntax and DNS/MX checks, serving verified data with per-tenant isolation.

Enables MCP clients to delegate analytics questions, sample-size calculation, knowledge retrieval, and metric listing to a deterministic statistical engine over stdio JSON-RPC.

Exposes 21 tools that drive a CBB extraction pipeline end to end: starting and monitoring runs, pulling next requests and replying, building and linting boxes, running wiring/id-source/acceptance gates, and routing model calls with stats and policy. It also supports human adjudication — lexicon approval, superseding records, conflict resolution and quarantine rulings — plus doctor, capabilities and smoke diagnostics.

Enables AI assistants to audit, profile, and govern dbt projects through natural language, including coverage scoring, schema drift detection, test suggestions, and non-destructive YAML documentation updates.

Enables AI assistants to audit dbt project health, profile data, detect schema drift, suggest tests, and auto-generate documentation through natural language. It consolidates coverage analysis, data profiling, and safe YAML updates into a single MCP interface.

Enables AI assistants to audit dbt project coverage and health, profile warehouse data, detect schema drift, suggest tests, and generate or safely update model documentation through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and auto-generate documentation and test suggestions through natural language. It provides tooling for coverage scoring, batched column statistics, and non-destructive schema.yml updates.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and auto-generate documentation through natural language. It combines coverage scoring, test suggestions, and non-destructive YAML updates in a single MCP server.

Enables AI coding assistants to assess dbt project health and test/documentation coverage, profile warehouse data, detect schema drift, suggest tests, and safely update schema.yml documentation through natural language.

Enables AI assistants to audit dbt project health and test coverage, profile data-warehouse columns, detect schema drift, and safely generate documentation and test suggestions into schema.yml files. It runs read-only warehouse queries and non-destructive YAML merges, all through natural-language conversation in Claude Desktop, Cursor, or other MCP clients.

It enables AI assistants to audit dbt project health, profile data, detect schema drift, suggest tests, and auto-generate documentation through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, suggest tests, and safely generate or update schema.yml documentation through natural language.

Enables AI assistants to audit dbt project quality, profile warehouse data, detect schema drift, and auto-generate or update documentation and tests through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, suggest tests, and auto-generate non-destructive schema documentation through natural language.

Enables AI assistants to audit dbt project quality, profile warehouse data, detect schema drift, suggest tests, and generate non-destructive schema.yml documentation through natural language.

Enables AI assistants to audit a dbt project's health, profile warehouse data, detect schema drift, and generate tests and documentation through natural language. It scores documentation and test coverage, recommends dbt tests from column profiling statistics, and non-destructively merges results into schema.yml files while preserving existing comments and formatting.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, recommend tests, and safely generate or update schema.yml documentation through natural language. It provides project scoring, coverage rankings, and non-destructive YAML edits while preserving comments and existing configurations.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and suggest tests through natural language. It also auto-generates documentation and safely merges updates into schema.yml files while preserving existing comments and formatting.

Enables AI assistants to audit project health, profile data, detect schema drift, and auto-generate documentation for dbt projects through natural language. It also provides coverage scoring, test suggestions, and safe schema.yml updates via MCP.

Enables AI assistants to audit dbt projects for documentation, test coverage, and naming health, profile warehouse data, detect schema drift against the manifest, and non-destructively generate or update schema.yml documentation and tests through natural language.

Enables AI assistants to audit dbt project quality, profile warehouse data, detect schema drift, and safely generate or update model documentation and tests through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, suggest tests, and safely generate or update model documentation through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and generate non-destructive schema.yml documentation and test suggestions through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, suggest tests, and generate documentation through natural language. It provides read-only analysis and non-destructive YAML updates for dbt projects.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and auto-generate or update model documentation and tests through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and safely generate or update dbt documentation and tests through natural language.

Enables AI assistants to audit dbt project health, profile data, detect schema drift, suggest tests, and safely generate documentation through natural language.

A Model Context Protocol server that enables large language models to access database metadata and perform cross-engine data querying across diverse database ecosystems.

A comprehensive MCP server for Dataiku DSS integration, providing Claude Code with direct access to manage recipes, datasets, and scenarios.

Enables interaction with the Unstructured API to manage data workflows, including creating and managing source connectors (S3, Azure, Google Drive, etc.), destination connectors (Weaviate, Pinecone, MongoDB, etc.), and workflows for document processing and data pipelines.