ai·rete·rag MCP server

• decideFree

  Make a deterministic, auditable decision in a domain. The verdict comes from the domain's rule set (Rete engine, never the LLM), so it is reproducible and compliant. The explanation is generated from the domain's ingested policy documents. Without an API key only the shared demo domains are available, and the response carries `next_step`: how to get a free key for your own rules. Pass that on to the user rather than dropping it. Args: domain: Rule-set domain, e.g. "loan", "fraud", "clinical". query: Natural-language question or decision request. facts: Structured facts for working memory, e.g. {"credit_score": 710, "annual_income": 85000}. Use `get_parameters` to see which fields a domain's rules test. Facts you read yourself from photos, document scans, voice notes or video go here, under those field names; explicit facts always win over anything extracted server-side. fact_sources: Where each fact in `facts` came from, e.g. {"monthly_income": "payslip.jpg", "claim_usd": "voice note 1"}. Always set this for facts you read from a file, photo, recording or video: it is stored in the decision's audit record so a reviewer can tell typed facts from ones read off evidence. Facts without a source are recorded as "request". as_of: Read the domain's policy documents as of this day, as YYYY-MM-DD (default: today). Use the date a case was filed to decide it under the policy in force then; the rules themselves are always the current ones. unstructured_text: Optional free text (an application, a case note, a voice-note transcript, what a photo or video shows); facts are extracted from it automatically and merged. response_mode: "verdict_only" (fastest), "verdict_with_explanation", or "full_audit" (every rule evaluation + retrieved chunks, available on every plan including the free tier). rule_firings come back in causal order: a rule that matched a fact asserted by an earlier firing appears after it, with the derived facts listed under `asserted_facts`. filter_retrieval_with_rules: Pattern 01 — run the rules first and let a fired rule's `retrieval_scope` action narrow which documents the retrieval searches before it runs. extract_from_retrieval: Pattern 02 — parse the retrieved documents into facts and assert them into working memory, so rules fire on what was actually read (not just the facts you passed). The result's `missing_parameters` lists rule inputs that were not supplied but could still change the verdict, most decisive first. When it is non-empty, tell the user the verdict is provisional and ask for those facts; when it is empty, more facts cannot change the verdict.

• get_parametersFree

  List the input parameters a domain's rules decide on — the facts to collect before calling `decide`. Derived from your account's own copy of the rules, so it covers your custom domains too. Each parameter has its `field` name (the key to use in `facts`), `kind` (number / boolean / string), the `tests` rules make on it (e.g. >= 720 — match these units and scales), the `rules` and `verdicts` it can lead to, and `max_salience`. Parameters come most decisive first: those feeding the highest-salience rules, which win when several rules fire. Also returns every verdict the domain can reach.

• get_rule_sourceFree

  Fetch a domain's rule set as editable YAML (plus the parsed rules and whether you may edit it). Use this before `put_rules` to see the current rules. For a built-in demo domain you get your own copy's rules once you have edited it, otherwise the shared demo's.

• get_usageFree

  Show this account's decision usage, plan, and remaining monthly quota.

• import_policy_rulesFree

  Convert a written policy document into DRAFT decision rules (LLM-assisted). Returns validated draft rules (when/action, including chained asserts where the policy stages its determinations), derived rule→rule edges, and overlap warnings. Each returned rule carries a `citation` field holding the policy sentence it encodes (also summarized in the top-level `citations` map). Coverage runs the other way too: `uncovered_sentences` lists policy sentences no rule's citation points back to (out of `policy_sentence_count`), and `unverified_citations` names rules whose quote is missing or not found verbatim in the policy. Show both to the user: an uncovered sentence may need a rule; an unverified one may be a paraphrase that misstates the policy. `background_sentences` is the subset of uncovered sentences with no obligation language (definitions, preamble); lead with the others, but mention these too, since the split is a keyword heuristic. NOTHING IS SAVED: review the drafts (and show them to the user), then persist explicitly with `put_rules` — validate first with dry_run=true, and keep each rule's `citation` in the YAML you save so the audit trail back to the policy survives. Args: domain: Domain the rules are drafted for (an owned domain or a new name). policy_text: The policy document text (max ~50k characters).

• ingest_textFree

  Add policy/reference text to a domain's knowledge base. The text is chunked and embedded; explanations for future decisions in this domain will cite it. Creating a new domain claims it for your account (plan limits apply). Ingesting into a built-in demo domain gives your account its own copy of that demo (it counts as one of your domains); the shared demo others see is unchanged. On team plans, only the domain admin (the member who created the domain, or the subscription owner) can add documents. Documents can be dated. A decision only cites documents in force on its date, so a replaced policy is never quoted for a new decision. To publish a new version, ingest it under a new `source` with `supersedes` naming the old one: the old document stops applying on the new one's `effective_from` (today if not given), and the new one starts that day. A document can be superseded only once; to replace a successor, supersede the successor. Args: domain: Domain to ingest into (existing or new). text: The policy or reference text. source: Optional source name shown in the document list. effective_from: First day this document applies, as YYYY-MM-DD (default: always). effective_until: First day it no longer applies, as YYYY-MM-DD (default: no end). supersedes: Source name of the document this one replaces.

• list_documentsFree

  List the documents ingested into a domain's knowledge base.

• list_rulesFree

  List the decision rules for one domain (or all domains). Returns each rule's conditions — either a flat AND list (field / operator / value) or a `when` condition tree (nested all/any/not) — plus its verdict, salience, and any asserted facts (`action.assert`, the facts a rule produces for other rules to consume). `edges` lists the derived rule→rule dependencies: src asserts a fact type that dst's conditions test (forward chaining). Each rule may also carry `citation` — the policy sentence it encodes — which is what lets a decision be traced back to the source clause. Also includes overlap warnings. Use this to learn which fact fields a domain expects before calling `decide`.

• put_ruleswrite actionFree

  Create or replace a domain's rule set from YAML (self-serve rule authoring). The first save to a new domain claims it for your account (plan limits apply). Saving to a built-in demo domain saves your own copy of it, seeded from the demo; the shared demo others see is unchanged. Rules are validated before saving — set dry_run=true to validate without persisting. The response reports ok/errors, the parsed rules, and any overlap warnings. YAML format — a list of rules. Flat form (conditions are AND-ed): - name: "Approve" salience: 10 conditions: - type: loan field: credit_score op: ">=" value: 700 action: verdict: "APPROVED" reason: "Credit score meets threshold" Tree form — `when:` holds nested all/any/not condition groups, and an action may assert derived facts that other rules consume (forward chaining; the rule graph derives from these automatically): - name: "Sepsis Screen" salience: 30 when: all: - {type: clinical, field: temperature_f, op: ">=", value: 101.5} - any: - {type: clinical, field: wbc_count, op: ">", value: 12.0} - {type: clinical, field: bands_pct, op: ">", value: 10} action: verdict: "URGENT_ALERT" assert: - {type: sepsis_flag, fields: {severity: high}} - name: "Escalate" salience: 40 when: all: - {type: sepsis_flag, field: severity, op: "==", value: high} - {type: clinical, field: age, op: ">=", value: 65} action: verdict: "ADMIT_ICU" Use either `conditions:` or `when:` per rule, never both. `not` passes when the inner condition does not hold (including when the field is absent). Produce/consume cycles between rules are rejected at validation. An action may also carry `retrieval_scope: { <key>: <value> }` to narrow which documents retrieval searches (Pattern 01). A rule may also carry `citation:` — the policy sentence it encodes. It is stored with the rule and shown beside it in decision audits, so a verdict can be defended with the source language, not just the rule name: - name: "Decline Late Returns" salience: 20 citation: "Returns are accepted within 30 days of delivery." when: all: - {type: retail, field: days_since_delivery, op: ">", value: 30} action: verdict: "DENIED" IMPORTANT: when persisting drafts returned by `import_policy_rules`, copy each rule's `citation` through into this YAML. Dropping it silently loses the link from the decision back to the policy clause that justifies it. Args: domain: Domain to author (an owned domain, or a new name to claim). rules_yaml: The full rule set as YAML text. dry_run: Validate only, without saving.

• Code scan6 source files scanned25/25
• Live reliabilityremote reachable in 1307ms20/20
• Tool poisoning9 tool descriptions checked13/15
• Auth qualityOAuth resource metadata advertised on 40115/15
• Maintenancelast push 12 days ago15/15
• Maintainer identityendpoint served from the registry-verified namespace domain8/10

Safety score

96/100

higher than 97% of 1,299 Productivity servers

Tools

9

the typical Productivity server has 7

Tools that change things

11%

typical: 0%. Fewer write tools means less an agent can break

Uptime

100%

of our recent checks; the typical remote Productivity server answers 100%

Response time

588 ms

faster than 23% of 655 Productivity servers

Downloads a week

108

more than 58% of 427 Productivity servers with a package

ai·rete·rag: common questions

Is ai·rete·rag MCP server safe?

Yes, by our scan: it is graded A (96/100). Read the ai·rete·rag safety report

How do I install ai·rete·rag?

It runs remotely at ai-rete-rag.com. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.

Does ai·rete·rag need an API key?

No key to paste: it signs you in with OAuth when your client connects.

Is ai·rete·rag maintained?

The last commit was 15 days ago (2026-10-20). The latest release is v0.11.0.

Is ai·rete·rag up?

100% of our last 28 checks got an answer. We check remote servers about four times a day.

What can I use instead of ai·rete·rag?

Servers from other publishers that do the same job: loci MCP server, Apple Rag MCP server and Context7 MCP server.

How does ai·rete·rag compare with other Productivity MCP servers?

safety score 96/100 (higher than 97% of 1,299 Productivity servers); tools 9 (the typical Productivity server has 7); tools that change things 11% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.