Prodoscore launches MCP server for enterprise AI assistants

Prodoscore has launched an MCP server for enterprise AI assistants, making workforce intelligence available alongside data from other business software.

The server is built on Model Context Protocol, an open standard for connecting AI systems to external tools. Prodoscore said the standard is backed by Anthropic, OpenAI, Google and Microsoft.

Prodoscore described the launch as the first MCP server from a workforce analytics provider. The connector works with Claude, ChatGPT, Gemini and Copilot, and can sit alongside systems including Salesforce, Jira, Asana, HubSpot and Slack.

Workforce data has often remained separate from sales, finance and operational information, with organisations relying on dedicated dashboards and log-ins for employee activity metrics. Prodoscore is aiming to bring that information into the same queries businesses now direct to AI assistants.

For example, a sales manager could ask an AI assistant which representative closed the most deals in the previous quarter, then compare that result with daily work patterns. Similar uses extend to human resources and finance, including identifying lower engagement in teams with open roles or software licences with low employee usage.

How It Works

The connector is read-only and automatically applies existing role-based permissions. Prodoscore also said customer data accessed through the system is not used to train external AI models.

That design reflects a broader concern among corporate buyers over how AI tools handle internal business information. Access controls, limits on data sharing and a clear separation from model training have become central issues as companies expand generative AI across departments.

Prodoscore, based in Los Angeles, sells workforce and employee productivity analytics software. Its platform draws on activity data from workplace applications such as Google Workspace, Microsoft 365, CRM platforms, unified communications tools and other business systems.

The software captures thousands of daily activity points across those applications, according to Prodoscore. The data is used to give managers a view of work patterns and employee engagement across distributed and hybrid teams.

AI And Data

The release comes as businesses try to make AI assistants more useful by connecting them to a wider range of internal systems. Much of the recent focus has been on linking models to customer records, project data, documents and financial information, while workforce intelligence has remained a less common source in those workflows.

By using MCP, Prodoscore is aligning its product with an emerging connectivity layer gaining support among major AI developers. The protocol allows assistants to retrieve information from separate software tools in response to natural-language prompts, rather than relying only on data stored within a single application.

For companies using several software platforms, the practical appeal is the ability to ask one question across multiple systems rather than compare reports manually. That can matter in functions such as sales, human resources and finance, where managers often need to connect behavioural signals with business outcomes.

Sam Naficy, Chief Executive Officer of Prodoscore, said the company sees a gap between the growth of enterprise AI use and the limited role workforce information has played in those systems.

"Organisations aren't lacking data - they're lacking a way to connect it all together to see the full picture of a company and its workforce," Naficy said.

"With the MCP Connector, one question to an AI assistant returns an answer that spans a company's entire tech stack. That's how true business intelligence should work, and Prodoscore is the first workforce analytics provider to introduce an MCP server. Companies simply cannot have an educated AI transformation without Prodoscore's MCP, as it provides data, facts and granularity in a visible, engaging and thoughtful way," he said.

Prodoscore is backed by PSG Equity. The company said its software is designed for employee-centric analysis and has been used to monitor productivity trends without relying on narrow output measures.