Memory the agent actually consults.
CxMS Agent is OpenCxMS's own AI coding agent. It runs its own loop, so “consult memory, verify, then respond” is enforced at the gate rather than suggested from the side.
Same Cortex memory engine as CxMS Pro AI. Different layer of enforcement.
Why a separate agent
Every AI coding assistant on the market today runs the same default behavior loop: receive prompt, generate answer, act. Not: receive prompt, search memory, verify context, answer. That loop belongs to the model vendor and the host CLI, not to the memory layer bolted on top.
CxMS Pro AI pushes back on this as far as you can from outside the loop. Hooks fire synchronously through your host CLI's hook system. Sensitive writes get gated until source-of-truth has been verified. Context gets injected at session start. It's the strongest scaffolding possible without controlling the agent loop itself.
But the host's loop is still the host's loop. The agent can still ignore retrieved context in its reasoning. The gate blocks specific actions, not the underlying agent step.
CxMS Agent runs its own loop. When the agent is ours, the gate becomes enforcement, not suggestion.
How CxMS Agent works
A standalone AI coding agent built on the Cortex memory substrate. Python-primary. Three inference tiers. Same memory engine as CxMS Pro AI, in a different shape.
Memory consultation enforced
Before the agent acts on anything stakes-bearing, the loop checks the Cortex memory engine for relevant context, contradictions, and source verification. Not a hook on the side. A required step in the agent's own execution path.
Three inference tiers
Local Ollama for offline / cost-free. Hybrid for smart-routed cascading. Cloud (BYOK) for best raw capability on the hardest tasks. You choose, or let the Hybrid router choose for you.
Same Cortex engine
The Cortex memory database is shared with CxMS Pro AI. Same plain-markdown files, same KMAP refinement loop, same confidence tiers. Your memory follows you from your CLI sessions into Agent sessions.
Three inference tiers
Pick the tier that fits the work. The memory engine, hooks, and governance are the same across all three. Only the model layer changes.
Local
Runs on your machine
- Backend
- Ollama with Qwen3-Coder-30B (or other supported local models)
- Cost
- $0 per token
- Best for
- Privacy-sensitive code, offline work, cost-floor control
- Tradeoff
- Slower than cloud on the hardest tasks. Best for the 70-80% of work where local is plenty.
Hybrid
Smart-routed cascade
- Backend
- Routes between Local and Cloud based on task complexity
- Cost
- Mostly $0 (Local), Cloud calls billed via your BYOK key
- Best for
- Power users who want cost control without giving up cloud capability when it matters
- Tradeoff
- Routing decisions are conservative by default. Override per-session or per-task.
Cloud
BYOK across providers
- Backend
- Claude (Anthropic), OpenAI, Google, xAI, DeepSeek, Mistral, OpenRouter
- Cost
- Your BYOK provider rates only. We don't intermediate.
- Best for
- Hardest tasks, frontier reasoning, complex codebases
- Tradeoff
- Cost scales with usage. Internet required.
CxMS Pro AI vs CxMS Agent
Same memory engine. Different layer of intervention. Sibling products on the same substrate.
| Capability | CxMS Pro AI | CxMS Agent |
|---|---|---|
| Cortex memory engine + KMAP | Yes | Yes (shared DB) |
| Runs on your machine | Yes | Yes |
| Works with your existing AI coding CLI | 9 CLIs supported | Standalone (alternative to a CLI) |
| Layer of intervention | Hooks via host CLI | Owns the loop |
| Memory consultation | Suggested via context injection | Enforced at the gate |
| Write gating | Yes (PreToolUse blocks) | Yes (loop-native) |
| Local inference | Through host CLI | Native Ollama support |
| Smart-routed Hybrid inference | No | Yes |
| BYOK across multiple providers | Through host CLI | Native across 7+ providers |
| Status | Shipping today ($49) | In development |
Most users will run CxMS Pro AI today and adopt CxMS Agent for projects where loop-level memory enforcement matters more than the host CLI's other features. The same Cortex database is shared between them.
Engineering choices that matter
Python-primary developer surface
`pip install cxms-agent`. The Pydantic AI framework adapter is the Tier 1 integration. Most agent developers already live in the Python ecosystem; Python adoption beats engine convenience. The compiled memory engine sits underneath.
One-time purchase + BYOK
No SaaS as the primary mechanic. No inference reselling. You buy the agent once. You bring your own API keys (Cloud tier). You own your memory, your code, and your spend.
Cortex memory shared with CxMS Pro AI
Plain-markdown memory files. Same KMAP continuous classifier refinement. Same confidence tiers. Same contradiction detection. Your memory follows you from Pro sessions into Agent sessions, and back.
Audit trail at the loop level
Every reasoning step, every memory consultation, every gate check is logged. Useful for governance, compliance (EU AI Act takes full effect August 2, 2026), and for managed-operations use cases where certified operators need full accountability.
Use cases
CxMS Agent is built coding-first. The same agent supports several adjacent applications because the memory + audit + governance substrate is the same.
Coding with enforced memory
The primary use case. Agent reasoning passes through memory consultation by design. Corrections stick because they have to. Decisions persist because the gate looks for them.
Privacy / offline work
Local tier with Ollama runs entirely on your machine. Air-gapped environments. Code that can't leave the network. Cost-sensitive work where token bills accumulate.
Cost-controlled AI development
Hybrid tier defaults to Local for the 70-80% of tasks where local is plenty and routes Cloud only when complexity warrants. BYOK pricing means your spend is what your provider charges, not what we mark up.
Multi-agent orchestration
Multiple CxMS Agent instances coordinating on a project. Cross-instance memory sharing through the shared Cortex substrate. For enterprises and complex engagements.
Remote AI-assisted operations
Certified OpenCxMS operators delivering managed services through the local agent. Context audits, governance deployment, forensic collection, incident response. Full audit trail because the agent runs locally with logged reasoning.
SASM micro-agent architecture
The same agent codebase ports to the SASM hardware safety module's micro-agent layer. One memory engine, two deployment targets (developer machine + safety-critical hardware).
Pricing
One-time purchase across all three tiers. BYOK for Cloud and Hybrid. No SaaS. Specific pricing locked when CxMS Agent reaches early access. Optional memberships (cloud sync, fleet coordination, priority support) coming as a fast-follow.
Early access opens when Cortex v4.0 + KMAP foundation work completes and the agent is ready for first beta users.
Pricing target: one-time purchase under $200 for the base agent across all three tiers. BYOK additional for Cloud and Hybrid usage. Final pricing locked at early access.
FAQ
How is CxMS Agent different from CxMS Pro AI?
What are the three inference tiers?
Do I need a separate API key?
Why one-time purchase instead of subscription?
What language is CxMS Agent built in?
When does CxMS Agent ship?
Does CxMS Agent replace my existing AI coding CLI?
What about remote operations and certified operators?
Register Interest
Be first when CxMS Agent opens early access
CxMS Agent is in development. The Cortex v4.0 memory substrate it's built on is partially shipping today in CxMS Pro AI. Register your interest and we'll notify you when early access opens.