MCP Governance

    MCP Governance

    MCP servers don't just expose APIs. They give AI agents direct access to tools that retrieve records, modify systems, trigger workflows, and execute operational tasks across your enterprise environment.

    A single agent may interact with:

    Google Docs to read and update documents

    Salesforce to retrieve customer records

    GitHub to create pull requests

    Slack to send operational notifications

    Databases to query internal data

    Internal APIs to trigger business workflows

    Each MCP server exposes specific tools agents invoke during execution, such as:

    read_documentwrite_documentcreate_pull_requestsearch_accountsquery_database

    Traditional AI governance focuses on prompts and outputs. That doesn't help when the risk isn't what the model says, it's what the agent does through MCP tools.

    Trussed governs MCP interactions at the execution layer, evaluating policy before every tool invocation, data request, workflow action, and system interaction.

    Are your MCP integrations properly governed?