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@run-iq/mcp-server

@run-iq/mcp-server

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@run-iq/mcp-server

An MCP server that gives LLM clients (Claude Desktop, Claude Code, Cursor, VS Code...) access to the Run-IQ rule engine. The model can write rules, validate them, and evaluate them against test inputs. It runs over stdio.

Install

The package is published to GitHub Packages. Point the @run-iq scope at it in your ~/.npmrc (GitHub requires a token with read:packages):

@run-iq:registry=https://npm.pkg.github.com
//npm.pkg.github.com/:_authToken=YOUR_TOKEN

Then add it to your client's MCP config:

{
  "mcpServers": {
    "run-iq": {
      "command": "npx",
      "args": ["-y", "@run-iq/mcp-server", "--plugins-dir", "/path/to/plugins"]
    }
  }
}

Requires Node.js 20 or later.

Related MCP server: AWS Pricing Calculator MCP Server

Plugins

The server starts with no calculation model. Load plugins with:

Flag

--plugins-dir <dir>

Imports every .js / .mjs file in the directory

--plugin <package>

Imports an npm package, resolved from the current directory, then from ~/.run-iq/mcp-plugins. Missing @run-iq/* packages are installed there automatically

Both flags can be combined, and --plugin can be repeated. Each module must default-export a PluginBundle from @run-iq/plugin-sdk:

// plugins/fiscal.mjs
import { FiscalPlugin, fiscalDescriptor } from '@run-iq/plugin-fiscal';
import { JsonLogicEvaluator } from '@run-iq/dsl-jsonlogic';

export default {
  plugin: new FiscalPlugin(),
  descriptor: fiscalDescriptor,
  dsls: [new JsonLogicEvaluator()],
};

The packages it imports must be installed next to the file (for example npm install @run-iq/plugin-fiscal @run-iq/dsl-jsonlogic in the parent directory).

The descriptor tells the server which extra fields the plugin's rules need. create_rule, validate_rules, the schema://rules resource and the prompts are built from it. With the fiscal plugin, for example, create_rule requires jurisdiction, scope, country and category.

Tools

Tool

create_rule

Build a rule and compute its checksum

validate_rules

Check structure, checksum, model params and plugin fields

inspect_rule

Details on one rule: checksum, model, whether it is active at a date

create_checksum

SHA-256 of a rule or of a params object

list_models

Models provided by the loaded plugins, with their params

evaluate

Evaluate rules against an input

simulate

Evaluate the same rules against up to 20 inputs and compare

explain_result

Turn an evaluation result into a readable summary

The engine runs in dry-run, non-strict mode: nothing is persisted and meta.effectiveDate is optional. Rules with a wrong checksum are skipped with CHECKSUM_MISMATCH.

Pass dates to create_rule as full ISO strings (2025-01-01T00:00:00.000Z). With a date-only value like 2025-01-01, the checksum is computed on that string, and evaluate later skips the rule because it normalizes the date first.

Decision graph tools

These tools build and run decision graphs (@run-iq/dg): nodes that compute, fetch data, branch or merge, wired by edges.

Tool

design_graph

Build a graph one action at a time (add_node, add_edge, remove_node, remove_edge, set_meta, get_current, reset), kept per sessionId

validate_graph

Quick structural check without compiling

compile_graph

Compile a graph and keep it in memory under its hash

inspect_graph

Mermaid diagram, node counts, ports, root and leaf nodes

execute_graph

Run a graph, given inline or by hash, against an input

simulate_graph

Run the same graph against up to 10 scenarios

inspect_context

Per-node outputs and events of a past run, by requestId

explain_graph_result

Turn a past run into a readable summary

Compiled graphs and the last 20 runs live in memory for the session. Compute nodes are evaluated with no rules attached, so they output 0.

Resources and prompts

schema://rules

Rule schema, plugin fields, model params, input fields and examples

models://catalog

Documentation of the available models

plugins://loaded

Loaded plugins, DSLs and descriptors

schema://graph

Decision graph format: nodes, edges, ports, policies, merge, enrich and subgraph configs

graph://examples

Example graphs: linear, merge with enrichment, conditional branching

analyze-text prompt

Turn a text (law, regulation, policy) into rules. Args: source_text, optional country

domain-expert prompt

Answer a question using the loaded plugins' domain

orchestration-architect prompt

Design a decision graph from a requirement, optional country

License

MIT

This server cannot be deployed

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Maintenance

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