Catalyst Governance

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

Category
Visit Server

README

Catalyst MCP Server

Catalyst MCP server Glama

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:

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

Recommended Servers

playwright-mcp

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.

Official
Featured
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

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.

Official
Featured
TypeScript
Kagi MCP Server

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.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

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.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured