About Catalyst Governance
Catalyst is a hosted governance layer for AI agents that checks consequential actions against permission rules, routes proposals for human approval, and records decisions. It is intended for teams needing policy enforcement, compliance scans, and an audit ledger for agent activity.
Key features
- 01Pre-action permission checks
- 02Human approval workflows
- 03Four governance modes
- 04Compliance scans across eight frameworks
- 05Hash-linked action audit ledger
- 06Approval-event webhooks
Use cases
- 01Require approval before production deployment
- 02Block actions outside declared capabilities
- 03Audit Claude Code actions
- 04Scan activity against compliance frameworks
MCP support
Catalyst exposes governance tools through a hosted MCP server over Streamable HTTP and SSE. MCP clients can check actions, manage approvals, run compliance scans, and export the audit ledger.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://catalyst.stratogenic.ai/mcpclaude mcp add --transport http catalyst https://catalyst.stratogenic.ai/mcp{"mcpServers":{"catalyst":{"type":"http","url":"https://catalyst.stratogenic.ai/mcp"}}}Open in Cursor{"servers":{"catalyst":{"type":"http","url":"https://catalyst.stratogenic.ai/mcp"}}}Open in VS Code{"mcpServers":{"catalyst":{"type":"http","url":"https://catalyst.stratogenic.ai/mcp"}}}{"mcpServers":{"catalyst":{"serverUrl":"https://catalyst.stratogenic.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://catalyst.stratogenic.ai/mcpAuth requiredhttps://catalyst.stratogenic.ai/mcp/sseAuth requiredTools
31| Parameter | Type | Required | Description |
|---|---|---|---|
| items | array | Yes | |
| domain | any | No |
Details
From the project READMECatalyst MCP Server
Governance middleware for AI agents — hosted MCP server with both SSE and Streamable HTTP transports.
What it does
Catalyst puts a governance layer between your AI agent and consequential actions. Before your agent writes files, sends messages, deploys code, or calls external APIs, it checks in with Catalyst. Depending on your governance mode, actions are allowed, routed to a human for approval, or denied.
Core features:
- Pre-execution permission gates with a progressive trust model:
observe → advisory → proposal → strict - Human-in-the-loop approval flows — agents submit proposals, humans approve/decline
- Compliance scanning across 8 frameworks: GDPR, SOC 2, ISO 27001, HIPAA, PCI-DSS, EU AI Act, Bribery Act, AML/KYC
- Hash-linked audit ledger — every agent action is recorded with
touched_by.source=mcp - Webhook notifications for
proposal.accepted/proposal.declinedevents
Use with Claude Code
Claude Code is a primary use case Catalyst was designed for. Claude Code governs itself session-locally — it asks before running dangerous commands, but those decisions leave no audit trail, survive no context reset, and sit outside your organisation's approval workflows.
Catalyst externalises that governance. Once connected, every consequential action Claude Code attempts is routed through your policy, logged in an immutable ledger, and (if required) held for human approval in the Catalyst dashboard before Claude Code proceeds.
Connect in one command:
claude mcp add catalyst \
--transport sse \
--url https://catalyst.stratogenic.ai/mcp/sse \
--header "X-API-Key: SGC_your_key_here"
Or with Streamable HTTP (Claude Code 0.10+):
claude mcp add catalyst \
--transport http \
--url https://catalyst.stratogenic.ai/mcp \
--header "X-API-Key: SGC_your_key_here"
Claude Code will automatically call catalyst_check_action before destructive operations and catalyst_await_approval when a proposal is required. Every action is ledgered with touched_by.source=mcp — you get a permanent, verifiable record of what your AI coding agent did and when.
What governance looks like in practice:
| Claude Code action | Catalyst response (proposal mode) |
|---|---|
git push --force | proposal_required — held for approval |
rm -rf ./dist | allow — whitelisted build action |
| Deploy to production | proposal_required — held for approval |
| Edit source files | allow — within declared capabilities |
| Call external API | proposal_required — undeclared capability |
Set your governance mode to observe to start with a full audit trail only, advisory to flag deviations without blocking, proposal to require human sign-off on sensitive actions, or strict to allow only explicitly whitelisted capabilities.
Get your API key at catalyst.stratogenic.ai.
Connect
Streamable HTTP (preferred — required by Glama, Smithery, and newer clients):
{
"mcpServers": {
"catalyst": {
"url": "https://catalyst.stratogenic.ai/mcp",
"transport": "http",
"headers": { "X-API-Key": "<your-key>" }
}
}
}
SSE (for clients that don't yet support Streamable HTTP):
{
"mcpServers": {
"catalyst": {
"url": "https://catalyst.stratogenic.ai/mcp/sse",
"transport": "sse",
"headers": { "X-API-Key": "<your-key>" }
}
}
}
Get your API key at catalyst.stratogenic.ai.
Tools
| Tool | Description |
|---|---|
catalyst_my_governance | Show your governance profile and plan capabilities |
catalyst_check_action | Check if a capability is permitted before acting |
catalyst_log_task | Record a task or action into the governance pipeline |
catalyst_pending_approvals | List proposals awaiting human sign-off |
catalyst_await_approval | Poll a specific proposal's approval status |
catalyst_register_approval_webhook | Register a callback URL for approval events |
catalyst_run_compliance_scan | Run an automated compliance scan (requires add-on) |
catalyst_list_compliance_frameworks | List available compliance frameworks |
catalyst_get_dashboard | Get the governance dashboard snapshot |
catalyst_export_ledger | Export the hash-linked audit chain |
Governance loop
catalyst_my_governance() # understand your mode + capabilities
↓
catalyst_check_action("write_file") # allow | proposal_required | deny
↓ if proposal_required
catalyst_log_task("Deploy to prod") # creates proposal, returns proposal_id
↓
catalyst_await_approval(proposal_id) # poll until approved: true
↓ proceed
Links
- Homepage: catalyst.stratogenic.ai
- Smithery: smithery.ai/servers/markjsmith311/catalyst
- Official MCP Registry: registry.modelcontextprotocol.io
- mcp.so: mcp.so/server/catalyst-governance
- Glama: private gateway connector — 31 tools via Streamable HTTP
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.