Catalyst 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.declined events

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:

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

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