Catalyst Governance
Catalyst puts a governance layer between AI agents and consequential actions. Before your agent writes files, sends messages, deploys code, or calls external APIs, it checks in with Catalyst. Depending on your policy, actions are allowed immediately, routed to a human for approval, or denied. Includes 8 pre-built compliance framework packs (GDPR, SOC 2, ISO 27001, HIPAA, PCI-DSS, EU AI Act, Briber
README
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.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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.