Traceforce
Device-layer AI security that maps and controls what Claude, ChatGPT, Copilot, and coding agents actually do
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www.traceforce.aiAbout Traceforce
Traceforce is an AI security and control platform that operates at the device layer rather than on the network. The observation behind it is that AI usage has moved out of the browser — Claude, ChatGPT desktop, Copilot, Cursor, and Codex all run as native applications or CLI tools, and a security stack that inspects browser traffic simply cannot see what they do. Traceforce runs an agent on the device, which is where it can watch actions as they happen and control them. Capabilities include risk assessment across 900+ AI apps and MCP servers, sensitive-data leakage detection in Claude, ChatGPT, and Copilot, and detection of dangerous actions taken by coding agents including Claude Code, Cursor, and Codex — the category of thing where an agent decides to delete a directory or push a secret and nobody finds out until later. All telemetry is reachable through an API rather than being locked in a dashboard. The paid tier adds runtime control over Claude Cowork and ChatGPT desktop, admin controls for connectors, and an MCP registry with a security approval process, which is the piece that turns shadow-MCP sprawl into something reviewable. The company also publishes an open-source MCP scanner. Pricing is per device, and the free trial covers 10 devices for 30 days with no card.
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Key Features
Traceforce Pros & Cons
✅ Pros
- +Device-layer coverage catches desktop and CLI agents that network tools miss
- +MCP approval registry addresses shadow-MCP sprawl directly
- +Free trial covers 10 devices with full telemetry API access
⚠️ Cons
- −The Pro per-device rate isn't published, so budgeting requires a sales call
- −Endpoint agents need deployment and management on every machine
- −Employees may read device-level monitoring as surveillance
Who Is Traceforce Best For?
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