mcpField
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ai·rete·rag

ai·rete·rag

Remote
ai-rete-rag.comAI & Agents0Updated 1w ago

About ai·rete·rag

ai·rete·rag is an MCP server for decisions based on auditable domain rules. A Rete engine produces each verdict, while an LLM explains it using ingested policy documents.

Key features

  1. 01Decide cases using domain rules
  2. 02Explain verdicts from policy documents
  3. 03Import policy text and manage rules
  4. 04Inspect rule conditions and source YAML
  5. 05Track fact sources and missing parameters
  6. 06Check account quota usage

Use cases

  1. 01Evaluate a loan application against underwriting rules
  2. 02Draft and review rules from policy documents
  3. 03Collect case details that could change a verdict
  4. 04Consult policies effective on an earlier date

MCP support

The MCP server provides tools for decisions, rule management, policy ingestion, and usage checks, along with a case-decision workflow prompt. It can be reached through a hosted URL or run locally.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://ai-rete-rag.com/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://ai-rete-rag.com/mcpAuth required
Streamable HTTPhttps://ai-rete-rag.com/mcp/authAuth required
Packages
pypiai-rete-rag-mcp0.11.0

Tools

9
ParameterTypeRequiredDescription
as_ofanyNo
factsanyNo
querystringYes
domainstringYes
fact_sourcesanyNo
response_modeenumNoverdict_only | verdict_with_explanation | full_audit
unstructured_textanyNo
extract_from_retrievalbooleanNo
filter_retrieval_with_rulesbooleanNo

Details

From the project 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

ToolWhat it does
decideMake 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). as_of reads the policy documents in force on an earlier day
get_parametersThe facts a domain's rules decide on (from your account's own rules), most decisive first — what to collect before decide
list_rulesInspect a domain's rules — conditions, verdicts, salience, overlaps
get_rule_sourceFetch a domain's rule set as editable YAML
import_policy_rulesTurn a written policy document into draft rules, each citing the sentence it encodes (nothing is saved — review, then put_rules)
put_rulesCreate or replace a domain's rule set from YAML (dry_run to validate)
ingest_textAdd policy text to a domain's knowledge base, optionally dated (effective_from, effective_until) or replacing an earlier version (supersedes)
list_documentsBrowse a domain's ingested documents
get_usageCheck your plan and remaining monthly decision quota

Prompt: decide_case

An agent workflow for deciding a case in any domain on your account, including your own: it calls get_parameters to learn which facts the rules decide on, reads the case — text, photos, document scans, voice notes or video (the agent reads the media itself; the API only receives the facts) — maps it onto those exact fields, calls decide with fact_sources recording which file each fact came from (kept in the decision's audit trail), and — while the result's missing_parameters is non-empty (facts that could still change the verdict) — asks you for them, most decisive first, and decides again. The verdict always comes from the rules.

Connect by URL (no install)

The server is also hosted, which is the only route for clients that connect to a URL and have no field for a static header — claude.ai and Claude Desktop custom connectors, in particular.

URLAuthReaches
https://ai-rete-rag.com/mcp/authSign in with Google, once, in the browserYour account — your domains, your plan quota
https://ai-rete-rag.com/mcpNone, or Authorization: Bearer ik_...Shared demo domains anonymously; your account with a key

Add https://ai-rete-rag.com/mcp/auth as a custom connector and approve the prompt. Connections are listed under Settings → Connected apps, and disconnecting one takes effect immediately.

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.)

Or skip the install entirely and point it at the hosted endpoint with your key:

claude mcp add --transport http ai-rete-rag https://ai-rete-rag.com/mcp \
  --header "Authorization: Bearer ik_your-key-here"
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:

VariableDefaultPurpose
AI_RETE_RAG_API_KEY(none)Your API key — authenticates calls and ties them to your plan quota
AI_RETE_RAG_API_URLhttps://ai-rete-rag.comAPI 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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