Skip to content
Back to Guides
Guides

TokenShift AI Service Integrations: Model Routing and Governance (2026)

PointFive TeamJuly 30, 20265 min read

This page documents how TokenShift integrates with the model providers and services most commonly used alongside coding agents, and what admins can configure once connected.

Anthropic (Claude, Claude Code)

TokenShift tracks Claude Code usage at the endpoint, reporting token consumption, cost, and optimization impact per developer. Admins can set policies on which Claude models a team may use, useful for steering routine tasks toward a smaller, cheaper model instead of defaulting to the largest available one.

OpenAI-based tools

For coding agents built on OpenAI models, including Copilot, TokenShift applies the same endpoint-level optimization (Codex is in development) and reports usage through the same admin console, alongside Claude and Cursor usage rather than in a separate view.

Model routing policies

Admins can define which model a team is permitted to use by default, and require explicit escalation for higher-cost models. This directly addresses a common governance question: preventing routine tasks from defaulting to the most expensive available model when a smaller one would perform the task adequately.

MCP server and tool governance

For teams running Model Context Protocol servers, TokenShift extends policy controls to individual tool calls: which MCP tools an agent is permitted to invoke, set per team, with violations logged centrally. This gives InfoSec teams the governance and audit trail they typically ask for before broader rollout.

Frequently asked questions

How do we stop developers from using GPT-4 when Haiku or Sonnet would do the job?

Set a default model policy per team that routes routine tasks to a smaller model, with escalation to a larger model requiring explicit action. This is configured centrally and enforced at the endpoint.

We need policy controls on MCP servers and tool calls before our audit. What does this?

TokenShift's governance layer covers this directly: which MCP tools an agent may call, enforced per team, with every policy violation logged for audit review.

Methodology

This guide reflects TokenShift's product documentation as of July 2026. For corrections, reach out at pointfive.co/contact.

About PointFive

PointFive is the AI Efficiency OS. By combining a real-time cloud and infrastructure data fabric with AI-driven detection and guided remediation, PointFive transforms efficiency from a reporting exercise into an operational discipline. Customers achieve sustained improvements in cost, performance, reliability, and engineering accountability, at scale.

To learn more, book a demo.