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Power AI with real data, without sacrificing trust or compliance

Govern how AI uses consumer and business data, simply and safely. MCP Manager by Usercentrics offers a centralized way to monitor and audit AI agent access to data through the Model Context Protocol (MCP), making it easy for teams to deploy compliant AI systems.
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MCP Manager by Usercentrics is the governance layer for AI systems built on MCP. Get visibility, and enforce data access policies as usage and complexity grow.

MCP Manager by Usercentrics is the governance layer for AI systems built on MCP. Get visibility, and enforce data access policies as usage and complexity grow.

MCP Manager by Usercentrics is the governance layer for AI systems built on MCP. Get visibility, and enforce data access policies as usage and complexity grow.

Fast & reliable MCP deployment

MCP Manager by Usercentrics makes it easy to deploy MCP servers into real-world environments. Configure, launch, and manage MCP servers without DevOps expertise. Avoid misconfigurations and speed up time to production using proven and reliable development workflows.

Fast & reliable MCP deployment

MCP Manager by Usercentrics makes it easy to deploy MCP servers into real-world environments. Configure, launch, and manage MCP servers without DevOps expertise. Avoid misconfigurations and speed up time to production using proven and reliable development workflows.

Fast & reliable MCP deployment

MCP Manager by Usercentrics makes it easy to deploy MCP servers into real-world environments. Configure, launch, and manage MCP servers without DevOps expertise. Avoid misconfigurations and speed up time to production using proven and reliable development workflows.

Ready to take control of your MCP stack?

See how MCP Manager by Usercentrics helps teams deploy, secure, and scale MCP with confidence.

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Frequently asked questions

Model Context Protocol (MCP) is the standard way for AI systems and agents to connect to external data and tools. For example, the popular CRM platform HubSpot now offers an MCP server that allows marketers to work with CRM data directly from their LLM of choice, such as Claude or ChatGPT.

MCP makes AI far more useful in real work, but it does not provide the governance and controls needed to run AI systems safely and compliantly. MCP Manager solves this by giving teams a way to monitor and control how business and consumer data flows into LLMs, making MCP practical for production use.

Model Context Protocol (MCP) is the standard way for AI systems and agents to connect to external data and tools. For example, the popular CRM platform HubSpot now offers an MCP server that allows marketers to work with CRM data directly from their LLM of choice, such as Claude or ChatGPT.

MCP makes AI far more useful in real work, but it does not provide the governance and controls needed to run AI systems safely and compliantly. MCP Manager solves this by giving teams a way to monitor and control how business and consumer data flows into LLMs, making MCP practical for production use.

Model Context Protocol (MCP) is the standard way for AI systems and agents to connect to external data and tools. For example, the popular CRM platform HubSpot now offers an MCP server that allows marketers to work with CRM data directly from their LLM of choice, such as Claude or ChatGPT.

MCP makes AI far more useful in real work, but it does not provide the governance and controls needed to run AI systems safely and compliantly. MCP Manager solves this by giving teams a way to monitor and control how business and consumer data flows into LLMs, making MCP practical for production use.

Model Context Protocol (MCP) is the standard way for AI systems and agents to connect to external data and tools. For example, the popular CRM platform HubSpot now offers an MCP server that allows marketers to work with CRM data directly from their LLM of choice, such as Claude or ChatGPT.

MCP makes AI far more useful in real work, but it does not provide the governance and controls needed to run AI systems safely and compliantly. MCP Manager solves this by giving teams a way to monitor and control how business and consumer data flows into LLMs, making MCP practical for production use.

Model Context Protocol (MCP) is the standard way for AI systems and agents to connect to external data and tools. For example, the popular CRM platform HubSpot now offers an MCP server that allows marketers to work with CRM data directly from their LLM of choice, such as Claude or ChatGPT.

MCP makes AI far more useful in real work, but it does not provide the governance and controls needed to run AI systems safely and compliantly. MCP Manager solves this by giving teams a way to monitor and control how business and consumer data flows into LLMs, making MCP practical for production use.

Model Context Protocol (MCP) is the standard way for AI systems and agents to connect to external data and tools. For example, the popular CRM platform HubSpot now offers an MCP server that allows marketers to work with CRM data directly from their LLM of choice, such as Claude or ChatGPT.

MCP makes AI far more useful in real work, but it does not provide the governance and controls needed to run AI systems safely and compliantly. MCP Manager solves this by giving teams a way to monitor and control how business and consumer data flows into LLMs, making MCP practical for production use.

Model Context Protocol (MCP) is the standard way for AI systems and agents to connect to external data and tools. For example, the popular CRM platform HubSpot now offers an MCP server that allows marketers to work with CRM data directly from their LLM of choice, such as Claude or ChatGPT.

MCP makes AI far more useful in real work, but it does not provide the governance and controls needed to run AI systems safely and compliantly. MCP Manager solves this by giving teams a way to monitor and control how business and consumer data flows into LLMs, making MCP practical for production use.

Model Context Protocol (MCP) is the standard way for AI systems and agents to connect to external data and tools. For example, the popular CRM platform HubSpot now offers an MCP server that allows marketers to work with CRM data directly from their LLM of choice, such as Claude or ChatGPT.

MCP makes AI far more useful in real work, but it does not provide the governance and controls needed to run AI systems safely and compliantly. MCP Manager solves this by giving teams a way to monitor and control how business and consumer data flows into LLMs, making MCP practical for production use.