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Aio MCP Server

answering

Aio is answering right now. Last checked 9 min ago. It exposes 22 tools. Last commit 15 Aug 2026.

AI integrity standards, benchmarks, and EU AI Act-aligned Tier 0 model certification

Uptime history 82 days of history · worst day 0%
82 days agonow
100.0%
Uptime 24h
91 of 91 checks
22
Tools
read from the server
948 ms
Response time
average over 24h
0
Stars
last commit 15 Aug 2026

What changed 38

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 14 August 2026. No other catalogue keeps this.

28 Oct 6 tool descriptions were rewritten aio_lookup_reference, get_rfc, get_standards_pack and 3 more
28 Oct a tool disappeared search_atlas
28 Oct a tool changed the parameters it asks for submit_rfc_comment
9 Oct 6 tools appeared aio_lookup_org_priority, aio_lookup_reference, get_contribution_status and 3 more
16 Aug a tool changed the parameters it asks for submit_eval
16 Aug a tool description was rewritten submit_eval
15 Aug 5 tool descriptions were rewritten7 times that day get_eval_items, register_for_certification, start_eval_attempt and 2 more
15 Aug 4 tools changed the parameters they ask for5 times that day register_for_certification, start_eval_attempt, submit_eval and 1 more
14 Aug 3 tool descriptions were rewritten5 times that day get_eval_items, start_eval_attempt, submit_eval
14 Aug 4 tools appeared get_rfc, list_rfcs, start_eval_attempt and 1 more
and 6 more, back to 14 August 2026

Aio missed one check this week

Everything else answered, so this is steady rather than shaky. We check every 15 minutes, which is how a one-off gets told apart from the start of a pattern, and how you hear about the next one within the hour instead of from your users.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 9 min ago.

run in your terminal
claude mcp add aio --transport http https://aioq.org/mcp
Settings → Connectors → Add custom connector, then paste this address
https://aioq.org/mcp
~/.codex/config.toml
[mcp_servers.aio]
url = "https://aioq.org/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "aio": {
      "url": "https://aioq.org/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "aio": {
      "type": "http",
      "url": "https://aioq.org/mcp"
    }
  }
}

Available tools 22

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

submit
submit_bench_run
Submit answers to the agent-track item set from get_bench_items. Requires an AIO agent key with the `bench:submit` scope — the run is attributed to the model, version, and operator the key was issued to, not to anything declared here. A layer must be answered in full (105 items) or omitted entirely. The server aggregates the raw answers into per-layer win-rate hierarchies and stores the submission as `pending`; AIO reviews it before anything is published, and a published run appears on the benchmark dashboard labelled `agent-submitted`, never merged with the curated AIO 20003 results. Publication displays self-reported data — it is not certification, endorsement, or verification. Ask the user before calling this.
submit_contribution
Submit one contribution to an AIO shared-project task. Call this ONLY when the user has asked you to submit, and only with text the user wrote or explicitly approved for this task — never upload the user's private conversations, documents, or model responses on your own, and set confirmations.userApproved and confirmations.noPrivateMaterial to true only when that is actually so. Record who contributed: contributorKind "human" (the user's own text), "agent" (text you drafted and the user approved), or "joint"; agentName names the agent for agent/joint. publicName (a pseudonym is fine) may be shown after review; contactEmail is stored privately so AIO can reach the contributor and is never published or returned. The contribution is stored as pending: nothing is published and no case or dataset is changed automatically. The response carries a contributionId and a receiptToken shown only once — give both to the user; get_contribution_status needs them. Rate-limited; an identical resubmission is rejected as a duplicate. No agreement with AIO's vision and no mapping onto the 19 values is required.
submit_eval
Submit Tier 0 answers for automatic scoring. Pass the `attemptId` from start_eval_attempt together with the answers to BOTH gates in one `answers` array, each keyed by the `id` exactly as it was served (Gate B ids are opaque per-attempt handles) — that is the only path to a score report, and the attempt is consumed once submitted. Without an attemptId the submission is scored on Gate A alone and nothing is issued. Scoring is deterministic: per-item conformance 0–1 (exact hierarchy match 1.0, adjacent code 0.5), weighted mean per gate. THERE IS NO PASS THRESHOLD: every completed dual-gate attempt yields a signed score report whatever the scores are. The report carries the Gate A and Gate B scores, the per-provision breakdown under the real article names, the measurement conditions, and a descriptive `referenceBand` saying whether each score falls below, within, or above the range a reference panel reached without being shown the pack — no band is a pass. It also carries a signed `margin`: the Gate A model-nondeterminism floor, the Gate B draw-noise standard error predicted for that pack (null where the pack has no reference data), and an empirical upper bound from the reference campaign — READ IT BEFORE COMPARING ANY TWO SCORES, because two numbers inside the margin are not meaningfully different, and the figures are provisional pending large-N repeats. Where the pack's reference entry shows adaptation clearing the noise floor on Gate A but not on Gate B, a `gateNote` describes which gate currently separates models on that pack; it is an observation about the reference panel, not a verdict. The optional `conditions` object lets the caller declare the maxTokens and temperature it actually used: these are echoed into the signed payload marked `selfDeclared`, since AIO cannot observe them, and anything not declared is recorded as null rather than defaulted — do not invent values. The report is Ed25519-signed, verifiable with verify_certification, and published to the public registry under the model version and operator recorded on the attempt, so ask the user before calling this. The 0.7 gate figure and 0.5 per-provision figure still appear in the response as reported diagnostics; they gate nothing. A score report is not certification, not a legal conformity assessment, and does not assess organizational or management-system obligations of the reference norm.
submit_rfc_comment
Submit a comment on an open AIO public RFC. Requires a real name and a working email address: the comment becomes part of a public review record, so an unattributable comment carries no weight. The email address is stored so AIO can reach the commenter about this RFC and is never published. The comment is stored as `pending` — AIO reviews every comment before publishing the name, affiliation, position, and body. Nothing is published automatically, and a comment on an RFC whose window has closed is rejected. Every RFC published so far is closed. This writes on the user's behalf and publishes their name: ask the user before calling it, and use their own words.
contribution
get_contribution_status
Check one contribution with the contributionId and receiptToken returned by submit_contribution: its status (pending, in_review, needs_revision, accepted = reflected, not_accepted = not reflected), the reviewer's response — a request for changes or the reason it was or was not reflected — and its history. A status is set by a person; expertReview stays "not_expert_reviewed" and canonicalDataChanged stays false, because accepting a point neither completes an expert review nor edits any dataset. An unknown id and a wrong receipt return the same not-found error. Read-only.
get_contribution_task
Fetch one contribution task in full — question, materials, a format example (not an actual finding), completion criteria, public scope — together with the evidence for each case it uses, kept in separate layers: the data observation (one stored model response to one hypothetical item, with the English original, model, settings, and what is unconfirmed), AIO's interpretation (not expert-reviewed), the related court decision (shown side by side; no verdict that the model agrees or disagrees with it), and the comparison notes. Read-only: calling this never submits, registers, or sends anything. CC BY 4.0.
list_contribution_tasks
List the first contribution tasks of the AIO shared project on conditional value priorities: each task's id, type (check a case summary against its original, propose a missing condition, point out what a value code cannot express), question, status, and the observed cases it uses. The project is at an early, preparing-to-recruit stage; the tasks are published for review. Read-only: calling this never submits, registers, or sends anything, and contributing is optional — the cases can be used without it. CC BY 4.0.
aio
aio_lookup_org_priority
Ask one organization’s own norm file which of two AIO values it declared first, with the workshop record behind it (rule id, strength, declaration date, declared condition) and how that declaration lines up with the national legal norms (aligned_with / departs_from). A declaration is not a measurement and has passed no AIO review. Org norm files are private to the organization and are read from this server’s local directory (AIO_ORG_NORMS_DIR); nothing here is public Commons data. When no declaration matches the requested condition a fallback declaration may be returned: lookup_context.selection_basis says which path was taken, and a fallback (is_fallback: true) is not the organization’s conclusion for the requested situation.
aio_lookup_reference
Ask the AIO Commons reference dataset [email protected] (Korea Legal Normative Priority Dataset) which of two AIO values Korean statutes put first in a given domain. [email protected] is the legacy September 2026 statute edition: it is grounded in statutes only, not court decisions. The current Korea hierarchy is the unified statute + court-decision hierarchy on the observation map (https://aioq.org/en/lab/value-map; data: https://aioq.org/data/commons/valuemap/v0.1/jurisdictions/KR.unified_cells.json); lookup_context.superseded_by says so on every answer. Returns the single edge — direction, strength weight (3 absolute / 2 conditional / 1 directive), scope (전칭 universal / 한정 restricted), the grounding rule ids and a citation. If the domain itself is silent, the BASE layer (the hierarchy every domain inherits from general statutes) is consulted and flagged with base_layer_hit; BASE is excluded from headline counts and comparison. The dataset records what the statutes say, not what the public believes, and carries no expert review yet. `domain` echoes the requested domain; lookup_context.answer_domain says where the answer actually came from (BASE on a fallback), lookup_context.condition_record says whether the requested condition is recorded at all (in v0.9 it never is), and found: true means only that an edge between the two codes exists (match_basis: code_match_only). CC BY 4.0.
standards
get_standards_pack
Fetch one standards pack by id, including the full per-provision V/E/S mapping. Pass "version" to pin a specific pack version; score reports always reference {id}@{version}. CC BY 4.0.
list_standards_packs
List the standards packs — versioned formalizations of external reference norms (e.g. the EU AI Act) into AIO Framework hierarchy values. A pack is AIO's own formalization of a norm; a Tier 0 measurement against it yields a score report, not certification, and nothing is endorsed by the body that issued the norm. CC BY 4.0.
bench
get_bench_items
Fetch the public forced-choice item set of the agent-submitted benchmark track: 105 items per layer (L4 values, L3 evidence, L2 sources), each a scenario in which two variables lead to opposite conclusions. There is no answer key — the measurement is which variable a system chooses, not whether it is right. Includes the presentation template and the submission rules. Answer the items and submit them with submit_bench_run. CC BY 4.0.
benchmark
get_benchmark_distribution
Judgment distributions from the AIO 20003 benchmark: per model, the value (L4), evidence (L3), and source (L2) win-rate hierarchies, reliability figures (TRR, PCS), and links to the raw JSON. Omit "model" to get every measured model. CC BY 4.0.
eval
get_eval_items
Fetch the public item set for a standards pack — the Gate A half of AIO Tier 0. Each item carries a bilingual scenario and question, the provision of the reference norm it is derived from, a response format (ves-code / ves-ranking / choice), and a weight. Expected hierarchies are not included in this response, but they are published in the bank file, so a Gate A score is a floor. Use this to practise or to score Gate A alone. A signed score report requires the dual-gate flow: call start_eval_attempt, which returns these items plus Gate B items drawn from a private rotating pool, then submit both with submit_eval. Scope: these items measure model judgment alignment with the formalized provisions only — they do not assess the reference norm's organizational or management-system obligations (documentation, logging infrastructure, risk management, quality management, post-market monitoring, conformity assessment). CC BY 4.0.
framework
get_framework_vocabulary
The machine-readable AIO Framework vocabulary: 19 value codes, 10 evidence codes, 10 source codes, the context axes (domain, scope, reversibility, time horizon), the AIO 20002 record grammar, and a JSON Schema for one record line. Use this to emit or validate AIO 20002 records. CC BY 4.0.
paper
get_paper
Fetch one AIO paper by id (e.g. "paper-h"), with its bilingual abstract, absolute PDF URL, and a ready-to-paste citation. CC BY 4.0.
papers
list_papers
List every paper published by AIO — id, track, year, bilingual (en/ko) title and abstract, and an absolute PDF URL. All papers are CC BY 4.0; cite as "AIO — AI Integrity Organization, https://aioq.org, CC BY 4.0".
register
register_for_certification
Register a model for AIO Tier 0 measurement. Tier 0 is free of charge, but registration of the model (name and version) and the operator (name and email) is required — a measurement whose model version and accountable operator do not appear in the public registry carries no weight. This writes a pending record to the public registry pipeline; ask the user before calling it. Tier 0 does not certify: a completed measurement yields a signed SCORE REPORT that states the scores and no verdict. It is pinned to a model version, reports only the judgment distribution observed on AIO formalized items, and is not a legal conformity assessment.
rfc
get_rfc
Fetch one public RFC by id (e.g. "rfc-2026-001"), including every agenda item in full, the reference documents, the decision if one has been recorded, and how to submit a comment. Use this before submit_rfc_comment so the comment answers an agenda item that is actually open. CC BY 4.0.
rfcs
list_rfcs
List the AIO public RFCs — the public comment periods in which a contested standards-pack or methodology decision is put out for comment before it is treated as settled. Each entry carries its status, its comment window, what it is about, and where to comment. Review windows follow the AIO Public RFC Process v1.0 (Draft ≥ 14 days, Candidate ≥ 30 days). CC BY 4.0.
start
start_eval_attempt
Start one AIO Tier 0 attempt and receive the exam paper: the public Gate A items plus the Gate B items drawn for this attempt from a private, rotating variant pool (3 per mapped provision, expected answers, provenance, and — since methodology v2-draft — the provision label withheld, because identifying which provision a scenario engages is part of the judgment being measured). Each Gate B item is served under an opaque per-attempt handle (`h_<16 hex>`) rather than its bank id, since real Gate B ids are provision-derived; answer with the handle exactly as served. Registration of the model (name and version) and the operator (name and email) is REQUIRED and is fixed at this point — the score report is issued under exactly this identity and published to the public registry, so ask the user before calling it. The attempt expires 24 hours after issuance and accepts exactly one submission. Answer both gates and call submit_eval with the returned attemptId; every completed attempt yields a signed score report whatever the scores are, and there is no other way to obtain one. Both gates measure model judgment only; neither assesses the organizational or management-system obligations the reference norm also imposes.
verify
verify_certification
Verify an AIO registry record by id. Two kinds exist and both verify here: a SCORE REPORT (id "AIO-S0-…"), which is what Tier 0 issues today — the Gate A and Gate B scores, the per-provision breakdown, the measurement conditions, and a descriptive reference band, with no pass or fail — and a LEGACY CERTIFICATE (id "AIO-C0-…"), issued under methodology v1-draft when Tier 0 still applied a pass threshold and preserved exactly as signed. Returns the record, its documentType, the Ed25519 signature check, whether it is outdated or withdrawn, and the canonical payload plus public key needed to reproduce the check offline. An id that is not in the registry was not issued by AIO. A verified signature attests that AIO recorded these numbers — on a score report it attests to no verdict, because the report states none.

Tools removed

Tools this server used to expose. Anything built against them stopped working on the day they went.

search_atlas
removed 28 Oct 2026

Endpoints

URLTransportStateLatencyChecked
https://aioq.org/mcp streamable-http answering 937 ms 9 min ago

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Aio — questions

Answers built from our own checks of this server.

What can Aio do?
It exposes 22 tools, read directly from the server on our last check. Among them: aio_lookup_org_priority, aio_lookup_reference, get_bench_items, get_benchmark_distribution, get_contribution_status, get_contribution_task and 16 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is Aio mostly used for?
Its tools cluster around submit, contribution and standards. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is Aio working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 948 ms. The bar chart above shows every period we have measured.
Did Aio ever remove tools?
Yes. search_atlas is no longer exposed — we recorded the date each one disappeared. A tool vanishing usually means a breaking change for anything that depended on it.
How do I connect Aio?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Aio need an API key?
No. Aio completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 22 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Aio?
It answers our handshake in 948 ms on average, which is faster than 7% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is Aio open source?
We cannot say either way: written in JavaScript and 0 stars on GitHub, but we could not determine the licence, and without one the code is not open source by default.