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Policy before action

Stop AI agents before they take risky actions.

Cordum puts policy, approval, and redacted audit evidence in front of Claude Code, MCP tools, shell commands, workflows, and production changes.

Source-available core · Local Edge path available today · Managed fleet enforcement requires endpoint controls

Claude Code · pre-tool gate
Illustrative decision
$ kubectl apply -f deploy/prod.yaml
classifierproduction_change
policyREQUIRE_APPROVAL
evidenceredacted + hashed

Held before execution

An authorized reviewer can approve or reject this exact action hash.

Compatible frameworks and clouds

Works alongside the frameworks and clouds you already run

Logos indicate ecosystem compatibility, not shipped plugins.

Hover or focus this section to pause the scrolling integration list.

  • OpenAI
  • Anthropic
  • LangChain
  • AWS
  • Google Cloud
  • Azure
  • Hugging Face
  • LlamaIndex
  • Temporal
  • CrewAI
  • AutoGen
  • Mistral
  • Cohere
  • Vertex AI
  • Bedrock
  • n8n
  • Zapier

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One adoption path

Start with Edge. Scale to Platform.

Edge is the concrete first experience. MCP governance expands the boundary. The control plane becomes the shared backend as rollout grows.

Start here · Cordum Edge

Govern coding-agent actions locally

Put policy and approval in front of Claude Code shell commands, file changes, and governed MCP calls before side effects.

  • Claude Code hook and local agentd
  • Approval-bound retries
  • Redacted action evidence

Developer path available today

Start with Edge

Scale here · Cordum Platform

Centralize governance for agent fleets

Move shared policy, approvals, workflows, and audit into the control plane when local adoption becomes a team requirement.

  • Gateway, Scheduler, and Safety Kernel
  • Workflow approval gates
  • Customer-managed deployment

Platform backend for managed rollout

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The Problem

The dangerous moment is an action, not a prompt.

Coding agents and MCP clients can cross from suggestion into side effects in one tool call. A post-hoc log arrives too late.

A shell can become a production change

Coding agents can run kubectl, Terraform, Git, and deployment commands with the same credentials as the developer.

MCP turns tools into mutations

A useful tool call can also write files, change policy, or touch production state unless identity and approval travel with it.

Post-hoc logs are not a control

Finding a risky action after execution is evidence of what happened, not a way to prevent the damage.

The action boundary

Policy before the action. Evidence after it.

Start at the coding-agent boundary, expand across MCP calls, and centralize the same decision model for production agent jobs.

Coding-agent actions

Cordum Edge evaluates Claude Code shell and file actions at the hook boundary.

  • Allow, deny, require approval, or constrain
  • Bind approvals to exact action and input hashes
  • Export redacted evidence instead of raw prompts

MCP tool calls

Gateway authentication, tenant scope, and the opt-in MCP policy gate sit before tools/call.

  • Caller-scoped tool and resource discovery
  • Approval holds for governed mutations
  • Retry coordinates for resolved approvals

Production agent jobs

The platform centralizes policy and approval when local adoption grows into a shared fleet.

  • Safety checks before dispatch
  • Workflow approval steps
  • Searchable decision and run evidence
How It Works

Before the action runs—not after.

The same decision pattern follows an action from intent through policy, approval, execution, and redacted evidence.

1

Agent proposes an action

submit

Claude Code, an MCP client, or a production agent describes the intended action.

2

Cordum evaluates policy

check

Identity, tenant, target, risk, and policy context are checked before execution.

3

Risky work pauses

approve

The exact action is held until an authorized reviewer approves or rejects it.

4

Allowed work resumes

execute

Only an allowed or correctly approved action continues to its execution path.

5

Redacted evidence remains

audit

Decision context, hashes, and approval references stay available for review.

governed action
$ cordumctl edge claude -- --print "prepare the production deploy"

action       kubectl apply -f deploy/prod.yaml
policy       REQUIRE_APPROVAL
execution    held before side effects
evidence     redacted descriptor + action hash
The action stays held until policy and approval allow it to continue.

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Frequently Asked Questions

What does Cordum stop?
Cordum evaluates AI-agent actions before execution. Depending on policy, it can allow, deny, require approval, throttle, or constrain coding-agent actions, MCP calls, and platform jobs.
Where should a team start?
Start with Cordum Edge for a concrete Claude Code action boundary. Enable MCP governance as tool-call risk grows, then use the platform to centralize policy, approvals, workflows, and audit.
Is the local Edge wrapper an enterprise enforcement boundary?
No. The wrapper is a developer and demo path. Fleet enforcement also requires managed settings, endpoint controls, trusted binaries, and service or keychain credential bootstrap.
Is Cordum source-available?
Yes. The core is source-available under BUSL-1.1, while the CAP v2 protocol is Apache-2.0. Review the code and validate the operating model before rollout.

Your AI coding agent is about to run a dangerous command. Cordum stops it.

Start with the Claude Code action boundary. Expand to MCP governance. Bring the same policy and approval model into the platform when your rollout becomes shared infrastructure.

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