Most sales AI is currently hallucinating on a diet of bad data. While enterprise leaders dream of autonomous agents closing deals, the reality is grimmer: roughly 80% of CRM data is inaccurate or incomplete. When you ask an AI “Why is this deal stalling?”, it can only answer based on what a tired sales rep bothered to manualy log Friday afternoon.
People.ai just changed the math. By integrating the Model Context Protocol (MCP) into its SalesAI platform, the company is finally giving AI agents—from Claude to Microsoft Copilot—direct access to the “unstructured reality” of sales: the emails, the Slack pings, and the actual meeting transcripts that never make it into Salesforce.
| Attribute | Details |
| :— | :— |
| Impact Level | High (Revenue Operations & AI Strategy) |
| Difficulty | Intermediate (Requires MCP-compatible LLMs) |
| Key Benefit | Eliminates “Data Blindness” in AI Sales Agents |
| Tools Needed | People.ai SalesAI, Claude Desktop, or MS Copilot |
The Why: The “Context Gap” is Killing Your ROI
The industry is moving toward agentic workflows, but an agent is only as good as its situational awareness. Traditionally, if you wanted an AI to analyze a pipeline, you had to export CSVs or rely on stiff API integrations that only saw “Structured Data” (Close dates, Deal amounts).
The real signal lives in “Unstructured Data.” Did the champion stop responding to emails? Was the tone of the last Zoom call defensive? By adopting MCP—an open standard pioneered by Anthropic—People.ai allows your AI to “reach into” the data layer and grab this context in real-time. It moves AI from guessing based on a dashboard to reasoning based on a relationship.
How to Leverage the People.ai MCP Integration
If you’re running a revenue org, you don’t want your team jumping between five different tabs. Here is how to bring this intelligence into your existing workflow.
- Connect the Data Layer: Link your communication tools (Email, Calendar, LinkedIn, Slack) to the People.ai SalesAI Platform. Their patented matching engine automatically attaches these activities to the correct CRM opportunities without manual entry.
- Enable the MCP Server: Configure your AI interface (like Claude Desktop) to recognize the People.ai MCP server. This creates a secure, standardized bridge between the LLM and your proprietary sales data. This setup is a massive bet on the AI coworker, allowing the model to act as a functional member of your team.
- Query in Natural Language: Instead of looking at a report, ask your AI tool directly: “Analyze the ABC Corp deal. Based on the last three meetings, who are the detractors we haven’t identified in the CRM?”
- Execute via Workflow: Use the AI’s “Deep Reasoning” output to generate late-stage collateral or outreach plans that address the actual objections raised in transcripts, rather than generic templates. Much like Gemini 3 Deep Think, this process prioritizes complex logic and technical problem-solving over simple data retrieval.
💡 Pro-Tip: Use the matching technology to filter “noise.” Most AI struggle with “over-contextualization” (getting confused by too much data). People.ai’s NLP filters out sensitive non-business info before the AI sees it, saving you tokens and keeping your prompts focused only on high-signal revenue activities.
The Buyer’s Perspective: Is MCP the New Standard?
For a long time, sales tech was a “walled garden.” You used the AI that came with your CRM, or you didn’t use it at all. People.ai is betting on a “Composable AI” future.
By using MCP, they aren’t forcing you to use their specific chat interface. If your team loves Microsoft Copilot or Claude, you can keep them there. This functionality is enhanced by recent updates like Claude Computer Use, which allows the AI to interact with software interfaces directly. This makes People.ai less of a “tool” and more of a “data engine.” Compared to competitors who offer closed-loop systems, this open architecture is a massive advantage for enterprises like Red Hat, who are already seeing win rates jump by 50% by moving away from isolated data silos.
However, the burden of “acting” on the data still rests on the human. This isn’t a “set and forget” tool; it’s a high-fidelity lens for your best reps.
FAQ: What You Need to Know
What exactly is MCP in this context?
The Model Context Protocol (MCP) is an open standard that lets AI models (like Claude) safely and easily connect to data sources (like People.ai) without custom, brittle API code for every single task. To ensure the most accurate results, users can even employ a Model Council approach to compare outputs across different LLMs.
Does this mean my AI will read my personal emails?
No. The platform uses NLP-powered filtering to remove sensitive or personal content, ensuring the AI only receives business-relevant context.
How is this different from a standard Salesforce integration?
Standard integrations only see what’s in the CRM. This integration sees what should be in the CRM—the actual conversations and engagement patterns that haven’t been manually logged yet.
Ethical Note/Limitation:
While this integration provides superior data, it cannot account for “offline” or “in-person” verbal agreements that aren’t captured by digital communication tools, meaning a human “sanity check” is still mandatory for high-stakes forecasting.