@sensigo/realm-mcp
v0.7.0
Published
MCP server for Realm — exposes 7 tools for AI agent connections over stdio or HTTP.
Downloads
1,670
Maintainers
Readme
@sensigo/realm-mcp
@sensigo/realm-mcp — the Realm MCP server. Exposes 7 workflow tools over stdio or HTTP for AI agent connections (VS Code Copilot, Cursor, Claude, and any MCP-compatible agent).
Installation
# Standalone binary (for AI agent MCP config)
npm install -g @sensigo/realm-mcp
# Embedded library (for custom application integration)
npm install @sensigo/realm-mcpUsage — Standalone MCP server
Add realm-mcp to your MCP client configuration (VS Code, Claude Desktop, Cursor, etc.):
{
"mcpServers": {
"realm": {
"command": "realm-mcp"
}
}
}Requires workflows to be registered first via realm workflow register.
Usage — Embedded MCP server
Create and connect a Realm MCP server inside your own application using any MCP-compatible transport.
import { createRealmMcpServer } from '@sensigo/realm-mcp';
// StdioServerTransport comes from the MCP SDK, not from @sensigo/realm-mcp
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
const server = createRealmMcpServer(); // options?: RealmMcpServerOptions
const transport = new StdioServerTransport();
await server.connect(transport);API Reference
| Symbol | Description |
| ---------------------------------- | ------------------------------------------------------------------------------- |
| createRealmMcpServer(options?) | Creates the MCP server with all 7 tools pre-registered. Returns McpServer. |
| createDefaultRegistry() | Returns an ExtensionRegistry pre-populated with built-in adapters. |
| generateProtocol(workflow) | Generates a structured protocol description for a workflow. |
| RealmMcpServerOptions | Type — optional config: registry?, secrets?, workflowStore?, runStore?. |
| WorkflowProtocol, ProtocolStep | Types — output shape of generateProtocol. |
MCP tools exposed
list_workflows— list registered workflowsget_workflow_protocol— get step-by-step protocol for a workflowstart_run— start a new workflow runexecute_step— submit agent output for a step and advance the runsubmit_human_response— resolve a human gateget_run_state— check current run statecreate_workflow— dynamically register and start a workflow in one call
Full documentation
Full documentation: https://github.com/sensigo-hq/realm
