AI Agents Deserve Better Data
Tamr’s MCP server connects large language models (LLMs) and AI agents to governed, real-time master data, so they use and act on trusted context.
What Your Agents Can Do With Tamr
Tamr brings AI-native master data management (MDM) capabilities, such as entity resolution, enrichment, and data quality management, into agentic workflows through one open MCP connection—enabling teams to build reliable AI agents that evaluate, understand, and update data with precision and accuracy.
MCP Server Integration
Tamr’s bidirectional MCP server enables AI agents to retrieve master data and relationships, so business workflows—sales, service, collections, procurement—draw from complete, governed data in real time. Agents with write permissions can also make real-time updates to the master data.
Agents That Improve Data, Not Just Read It
Tamr’s curation agents surface duplicates, anomalies, and gaps—prioritized by Tamr AI—so stewards can focus on the most challenging data issues to improve data quality. Tamr matches, dedupes, and enriches the record, then propagates the verified version back to operational systems.
Bring Your Own Agent
With Tamr’s Bring-Your-Own-Agent (BYOA) architecture, you can plug AI agents specific to your workflows into Tamr’s mastering pipeline. Tamr can call these agents (such as a risk model or a custom classifier) when records change and react to what they write back.
Tamr’s In-Product AI Assistant
Whether reviewing a customer record, exploring entity relationships, or drafting personalized content, Tamr’s Integrated AI Assistant (TIA) securely leverages LLM technology to help users query, validate, and act on trusted data without digging or coding.
Tamr’s AI-Native Advantage in Action
In the startup world, change is constant. But one thing remains consistent: our values. We believe there’s a strong link between happy people and healthy startups, and we’re committed to building a safe and nurturing environment for our team. We do this through:
Make Your Data Talk
Empower business users with self-service access to insights and updates through a conversational UI, reducing reliance on data teams and accelerating day-to-day decisions.
Enterprise-Ready AI Agents
Tamr gives AI agents the power to act confidently with clean, governed data. Tamr’s MCP server connects decisions to trusted context—speeding execution, not increasing risk.
Fuel Better LLM Outcomes
An agent that asks about a top account shouldn’t find five conflicting records. Tamr resolves and enriches entities first, so outputs are relevant, accurate, and complete.
LLM Connectivity with MCP FAQs
Tamr’s bidirectional MCP server gives AI agents real-time access to master data and the relationships between records, so agentic workflows can draw on complete, governed information. With write permissions, agents can also update that master data directly.
Tamr reduces the chance for hallucinations, false responses, or misinformation by supplying unified, clean, and enriched mastered entities for downstream LLM consumption.
Tamr enables organizations to bring master data into LLM environments with multi-agent workflows via MCP integration, giving organizations a secure, governed way to leverage their trusted enterprise data. And with Bring-Your-Own-Agent (BYOA) architecture, you can connect trusted data to downstream workflow-specific agentic applications.
Tamr’s bidirectional MCP server is designed to provide a more dynamic and modern approach to data management compared to traditional data pipelines, which focus primarily on data query, data cataloging, and ETL. With the needs of business users in mind, Tamr’s MCP server enables the delivery of master data to LLMs in a consumable way via a modern, standard protocol.
Tamr’s AI Assistant can support tasks such as reviewing customer records, investigating relationships between entities, and drafting personalized content.
See for yourself
Get a free, no-obligation, 30-minute demo of Tamr, and discover how our unique AI-native MDM solution can empower you to deliver data you can trust.