Singular unlocks instant, secure LLM access to marketing data, just talk to Claude for live ROI, creative, and campaign insights. No code. No dashboards.

Singular, the leading marketing analytics platform, announced the launch of a new integration with Claude, Anthropic’s large language model (LLM), enabling marketers to query campaign performance data using natural language. This integration leverages the newly released Model Context Protocol (MCP), which provides a secure and standardized interface between enterprise-grade datasets and generative AI tools.

Speed is a competitive advantage, by connecting Claude to our normalized, analysis-ready datasets, we’re equipping teams with faster, more intuitive access to the insights that drive growth.”
— Gadi Eliashiv, CEO and co-founder at Singular

With this capability marketers can now retrieve answers to business critical questions such as: which ad partners deliver the highest ROI, where cost per install is rising, all without writing SQL or navigating dashboards.

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The integration marks the first deployment of MCP in the mobile measurement technology ecosystem. MCP acts as a secure bridge between enterprise data and LLMs, allowing models like Claude to deliver precise, contextualized responses without compromising data governance or performance. Singular plans to extend this support to additional LLMs including ChatGPT and Gemini as they adopt the MCP standard.

Key Capabilities:
Unified access to campaign, campaign, cost, and engagement data via Claude
Real-time performance updates with support for live campaign changes
Secure, governed architecture compliant with enterprise standards
Visualized outputs including charts and comparisons generated via natural queries

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The integration is now available to all Singular customers. Setup requires no code and can be completed in minutes via Claude’s integrations panel.

Singular’s analytics platform supports over 1,200 data connectors and includes advanced features for fraud prevention, SKAN modeling, creative performance analysis, and cross-platform attribution.