@run-iq/mcp-server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@@run-iq/mcp-serverevaluate rule for fiscal benefit with income 80000"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@run-iq/mcp-server
MCP (Model Context Protocol) server that exposes the Parametric Policy Engine (PPE) to LLMs. Connects to Claude Desktop, Cursor, VS Code, and any MCP-compatible client via stdio.
Plugin-aware: the server dynamically adapts its tools, resources, and prompts to whatever plugins are loaded — zero hardcoding required.
Installation
npm install -g @run-iq/mcp-serverOr run directly with npx:
npx @run-iq/mcp-serverConfiguration
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"run-iq": {
"command": "npx",
"args": ["@run-iq/mcp-server"]
}
}
}Cursor / VS Code
{
"mcpServers": {
"run-iq": {
"command": "npx",
"args": ["@run-iq/mcp-server"]
}
}
}Custom Plugins
The server is 100% domain-agnostic by default. You MUST attach plugins to give the AI engine capabilities. You can load plugins from NPM packages or from a local directory.
Option 1: Load from NPM (Recommended)
Provides dynamic imports directly from node_modules or global installations.
{
"mcpServers": {
"run-iq": {
"command": "npx",
"args": ["@run-iq/mcp-server", "--plugin", "@run-iq/plugin-fiscal", "--plugin", "@my-org/payroll"]
}
}
}Option 2: Load local bundles Load compiled javascript files from a local directory:
{
"mcpServers": {
"run-iq": {
"command": "npx",
"args": ["@run-iq/mcp-server", "--plugins-dir", "/path/to/plugins"]
}
}
}Each .js or .mjs file in the directory must export a PluginBundle:
import type { PluginBundle } from '@run-iq/plugin-sdk';
const bundle: PluginBundle = {
plugin: new MyPlugin(),
descriptor: myDescriptor,
dsls: [new MyDslEvaluator()],
};
export default bundle;Tools (8)
Tool | Description |
| Evaluate rules against input data (always dry-run) |
| Compare N scenarios side-by-side with the same rules |
| Verify rule structure, checksum, model params, and plugin fields |
| Generate a valid Rule JSON with auto-computed SHA-256 checksum |
| Analyze a single rule in detail (validity, active status, errors) |
| Human-readable explanation of an EvaluationResult |
| List available calculation models with parameter schemas |
| Compute SHA-256 checksum for a params object |
All tools with plugin-specific fields (e.g. create_rule, validate_rules) dynamically adapt their schemas based on loaded plugins.
Resources (3)
URI | Description |
| Complete rule schema: base fields, plugin extensions, model params, input variables, JSONLogic syntax, and examples |
| Markdown documentation of all calculation models with parameters and usage examples |
| Information about loaded plugins, DSL evaluators, and descriptor status |
Prompts (2)
Prompt | Description |
| Domain-specific expertise adapted to loaded plugins: scenario comparison, result explanation, recommendations |
| Translate regulatory/policy text into Run-IQ rule definitions with all required plugin fields |
Both prompts dynamically inject plugin metadata, guidelines, and examples.
Plugin-aware architecture
The server adapts to any loaded plugin through the PluginDescriptor contract (from @run-iq/plugin-sdk):
Plugin loads → descriptor provides metadata → server adapts everythingTools:
create_ruleadds plugin-required fields to its Zod schema.validate_ruleschecks plugin-specific constraints.Resources:
schema://rulesdocuments plugin extension fields, input variables, and examples.Prompts:
domain-expertbecomes a fiscal/social/payroll expert based on what's loaded.analyze-textinjects plugin-specific model guidance and examples.
Default behavior
By default, the server loads an empty engine. You must specify --plugin (NPM package) or --plugins-dir (local folder) to inject calculation models and rules. For example, passing --plugin @run-iq/plugin-fiscal provides the 6 standard tax calculation models.
Writing a custom plugin
A plugin describes itself via PluginDescriptor:
import type { PluginDescriptor } from '@run-iq/plugin-sdk';
export const socialDescriptor: PluginDescriptor = {
name: '@run-iq/plugin-social',
version: '0.1.0',
domainLabel: 'social',
description: 'Social benefits calculation plugin',
ruleExtensions: [
{ name: 'benefitType', type: 'string', required: true,
enum: ['ALLOCATION', 'AIDE', 'EXONERATION'], description: '...' },
],
inputFields: [
{ name: 'householdIncome', type: 'number', description: '...', examples: [150000] },
],
examples: [/* concrete rule examples */],
promptGuidelines: [
'Consider household composition when creating rules',
'Use THRESHOLD model for means-tested benefits',
],
};The MCP server will automatically expose benefitType in create_rule, validate it in validate_rules, document it in schema://rules, and inject the guidelines into prompts.
Safety
Always dry-run: the engine never persists snapshots — safe for AI experimentation
Read-only: no mutations to external state
Checksum verification: SHA-256 integrity checks on rule params
Requirements
Node.js >= 20
License
MIT — Abdou-Raouf ATARMLA
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