[ Confirm upstream transport MCP ]

How to Use Chronulus AI MCP Server with Bifrost

Predict anything with Chronulus AI forecasting and prediction agents.

[ MCP SERVER SUMMARY ]

Chronulus AI MCP server summary

Predict anything with Chronulus AI forecasting and prediction agents. Connect Chronulus AI through Bifrost MCP Gateway to centralize access control, virtual keys, and tool-call observability for your AI assistants.

Property	Details
Company	Upstream maintainer
Connection type	Confirm upstream transport
Authentication	Varies by upstream server
Package or endpoint	See upstream documentation
Capabilities	Chronulus AI tools over MCP, AI assistant connectivity, Governed tool access through Bifrost
Official documentation	Chronulus AI MCP documentation

Before you start

Review the Chronulus AI upstream documentation for its installation requirements
Obtain any credentials required by the upstream service
A running Bifrost MCP Gateway instance

What you can do with Chronulus AI

Predict anything with Chronulus AI forecasting and prediction agents.
Expose Chronulus AI tools to Claude, Cursor, and other MCP clients through one endpoint
Apply virtual keys, tool allowlists, and audit logging at the gateway

MCP ServerIntegration

[ HOW TO CONNECT ]

Connect Chronulus AI to Bifrost in three steps

Install Bifrost

Start the gateway locally or deploy in your VPC.

npx -y @maximhq/bifrost

Add Chronulus AI in MCP Gateway

Open MCP Gateway in the Bifrost dashboard, click New MCP Server, and select the transport documented by the upstream server. Or register via the API below.

• Confirm the transport, command or endpoint, and authentication requirements in the Chronulus AI upstream documentation.

• Replace every placeholder in the example before sending the request.

Point clients at Bifrost /mcp

Configure Claude Desktop, Cursor, or Claude Code to use your Bifrost endpoint with a virtual key instead of connecting directly to Chronulus AI.

{
  "mcpServers": {
    "bifrost": {
      "url": "http://localhost:8080/mcp",
      "headers": {
        "Authorization": "Bearer vk_your_virtual_key"
      }
    }
  }
}

[ EXAMPLE CONFIG ]

Register Chronulus AI via API

Add this MCP client with a POST to /api/mcp/client. See Connecting to MCP Servers for full options.

# For a remote HTTP or SSE server:
curl -X POST http://localhost:8080/api/mcp/client \
  -H "Content-Type: application/json" \
  -d '{
    "name": "chronulus-ai",
    "connection_type": "<http|sse>",
    "connection_string": "<upstream MCP endpoint>",
    "tools_to_execute": ["*"]
  }'

# For a local STDIO server:
curl -X POST http://localhost:8080/api/mcp/client \
  -H "Content-Type: application/json" \
  -d '{
    "name": "chronulus-ai",
    "connection_type": "stdio",
    "stdio_config": {
      "command": "<upstream command>",
      "args": ["<arg>"]
    },
    "tools_to_execute": ["*"]
  }'

[ WHY BIFROST ]

Run Chronulus AI through one governed gateway

Access control

Virtual keys, RBAC, and tool allowlists per team or agent.

Cost governance

Attribute MCP tool spend alongside LLM usage in one view.

Observability

Log every tool call with latency, server, and virtual key metadata.

Credential isolation

Upstream secrets stay in the gateway — not on every laptop.

[ FAQ ]

Common questions

What does the Chronulus AI MCP server do?

Predict anything with Chronulus AI forecasting and prediction agents. The exact tools available depend on the upstream server version and configuration.

How do I connect Chronulus AI to Bifrost?

Check the upstream documentation to determine whether Chronulus AI uses STDIO, Streamable HTTP, or SSE. Then add it as an MCP client in Bifrost using the corresponding command or endpoint.