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Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.
About
Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.
Security Report
This is a well-structured MCP server for the ai·rete·rag decision platform with proper authentication, minimal code complexity, and permissions that align with its purpose as an API client. The server requires API key authentication (with a secure fallback), handles credentials correctly via environment variables, and makes only intended network calls to the ai·rete·rag API. No malicious patterns, code injection vulnerabilities, or credential leaks were identified. Supply chain analysis found 5 known vulnerabilities in dependencies (0 critical, 5 high severity). Package verification found 1 issue.
4 files analyzed · 9 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
Environment variable: AI_RETE_RAG_API_KEY
Environment variable: AI_RETE_RAG_API_URL
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"com-ai-rete-rag-ai-rete-rag-mcp": {
"env": {
"AI_RETE_RAG_API_KEY": "your-ai-rete-rag-api-key-here",
"AI_RETE_RAG_API_URL": "your-ai-rete-rag-api-url-here"
},
"args": [
"ai-rete-rag-mcp"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
ai·rete·rag MCP Server
Use ai·rete·rag — deterministic rule-based decisions with RAG-powered explanations — from Claude Code, Claude Desktop, or any MCP client.
The verdict always comes from the Rete rule engine (auditable, reproducible); the LLM only explains why, grounded in your ingested policy documents.
Tools
| Tool | What it does |
|---|---|
decide | Make a decision in a domain — structured facts and/or free text, with optional Pattern 01 (rules scope retrieval) and Pattern 02 (retrieval into working memory) |
list_rules | Inspect a domain's rules — conditions, verdicts, salience, overlaps |
get_rule_source | Fetch a domain's rule set as editable YAML |
import_policy_rules | Turn a written policy document into draft rules, each citing the sentence it encodes (nothing is saved — review, then put_rules) |
put_rules | Create or replace a domain's rule set from YAML (dry_run to validate) |
ingest_text | Add policy text to a domain's knowledge base |
list_documents | Browse a domain's ingested documents |
get_usage | Check your plan and remaining monthly decision quota |
Install
No install needed with uv — uvx ai-rete-rag-mcp
fetches and runs the server on demand (see the config snippets below).
Alternatively, install it as a package:
pip install ai-rete-rag-mcp # from PyPI
pip install . # or from source, in this repo
Configure
First create an API key: sign in at ai-rete-rag.com,
open Settings → API Keys, and create a key (ik_... — shown once).
Claude Code
claude mcp add ai-rete-rag -e AI_RETE_RAG_API_KEY=ik_your-key-here -- uvx ai-rete-rag-mcp
(If you installed via pip, use -- ai-rete-rag-mcp instead of -- uvx ai-rete-rag-mcp.)
Claude Desktop / other clients (JSON)
{
"mcpServers": {
"ai-rete-rag": {
"command": "uvx",
"args": ["ai-rete-rag-mcp"],
"env": {
"AI_RETE_RAG_API_KEY": "ik_your-key-here"
}
}
}
}
(With a pip install, set "command": "ai-rete-rag-mcp" and drop "args".)
Environment variables:
| Variable | Default | Purpose |
|---|---|---|
AI_RETE_RAG_API_KEY | (none) | Your API key — authenticates calls and ties them to your plan quota |
AI_RETE_RAG_API_URL | https://ai-rete-rag.com | API base URL — point at http://localhost:8000 for local dev |
Without a key you can still explore the shared demo domains (loan, fraud,
clinical, …) subject to free-tier limits.
Example
"Use ai·rete·rag to decide whether this loan application should be approved: credit score 645, annual income $52k, requested amount $30k."
Claude calls decide(domain="loan", facts={...}) and returns the rule-derived
verdict plus a plain-English explanation citing the underwriting policy.
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