ara-rgaa-mcp
ara-rgaa-mcp provides an MCP interface to fully manage RGAA accessibility audits on the Ara platform from any MCP-compatible client (Claude Code, Codex, Cursor, etc.) without manual browser login.
Authentication
Log in via environment variables (JWT token or email/password) and refresh sessions when tokens expire.
RGAA Referential
List all RGAA criteria (filterable by audit type) and retrieve detailed criterion descriptions with tests from an embedded offline referential.
Audit Management
Create new audits (FULL: 106 criteria, FAST: 25 criteria, COMPLEMENTARY: 50 criteria), duplicate existing audits, retrieve full audit details, update metadata (procedure info, auditor details, environments, technologies, tools), update only notes, publish (irreversible), and soft-delete audits.
Criterion Evaluation
Update evaluation results for specific RGAA criteria across pages, setting compliance status (COMPLIANT, NOT_COMPLIANT, NOT_APPLICABLE, NOT_TESTED), user impact (MINOR, MAJOR, BLOCKING), and comments.
Results & Reporting
Retrieve all criterion results for an audit or a specific page, fetch the full public report (accessibility rate, distributions), and export results as CSV.
Accessibility Statement
Update and publish the official accessibility declaration (déclaration d'accessibilité), including environments, tools, technologies, and contact information.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ara-rgaa-mcpCreate a full audit for www.example.com with 5 pages"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Ara MCP Server — Audits RGAA via IA
Serveur MCP (Model Context Protocol) qui expose les opérations CRUD sur les audits d'accessibilité RGAA de la plateforme Ara. Permet de piloter un audit Ara entièrement depuis Claude Code, Codex ou tout client MCP compatible — sans login manuel dans le navigateur.
Projet communautaire, non officiel. Ce serveur est un client tiers de l'API d'Ara, le service d'audit d'accessibilité de la DINUM. Il n'est ni édité ni maintenu par la DINUM.
English — An MCP server for Ara, the French government platform for RGAA 4.1 accessibility audits. It exposes 17 tools to create, fill in, publish and export accessibility audits from any MCP client. Requires an account on ara.numerique.gouv.fr. Documentation is in French, matching the audience of the RGAA. Unofficial community project.
Installation
1. Se connecter, une fois :
npx ara-rgaa-mcp loginUne page s'ouvre dans votre navigateur, sur votre propre ordinateur. Vous y saisissez vos identifiants Ara ; le jeton est enregistré dans ~/.config/ara-rgaa-mcp/credentials.json, en permissions 600. Votre mot de passe n'est jamais enregistré.
2. Déclarer le serveur — sans aucun secret dans la configuration :
{
"mcpServers": {
"ara-rgaa": {
"command": "npx",
"args": ["-y", "ara-rgaa-mcp"]
}
}
}Prérequis : Node.js ≥ 18 et un compte sur ara.numerique.gouv.fr.
Pour Claude Code, le fichier est ~/.claude/claude_desktop_config.json. Pour Codex ou Cursor, même format dans leurs réglages MCP respectifs.
Le renouvellement est automatique. Les jetons d'Ara durent 24 h, mais le serveur en demande un neuf à chaque démarrage : un usage régulier ne redemande jamais de se connecter. Après plus de 24 h sans usage, le serveur vous dit de relancer login.
Commande | |
| Se connecter et enregistrer le jeton |
| Compte, instance, âge du jeton |
| Supprimer le jeton enregistré |
Une page locale qui réclame des identifiants ressemble à du hameçonnage : le serveur prend donc quatre précautions.
Il écoute uniquement sur
127.0.0.1, jamais sur une interface réseau.L'URL comporte un jeton aléatoire qu'une autre page locale ne peut pas deviner ; toute autre adresse renvoie 404.
Elle est à usage unique : le serveur s'arrête dès la connexion réussie.
L'URL exacte est affichée dans le terminal — comparez-la à celle du navigateur avant de saisir quoi que ce soit.
Votre mot de passe ne transite que du navigateur vers ce processus local, puis vers ara.numerique.gouv.fr. Il n'est écrit nulle part.
Si vous n'avez pas lancé la commande vous-même, fermez la page.
Related MCP server: HackerOne MCP Server
Authentification par variables d'environnement
Alternative à login, pour l'automatisation ou les environnements sans navigateur.
Variable | Défaut | Description |
| — | Jeton JWT. ⚠️ Valable 24 h seulement |
| — | Email, pour l'authentification au démarrage |
| — | Mot de passe, pour l'authentification au démarrage |
|
| URL de base de l'API Ara |
Les identifiants ne sont jamais acceptés en paramètres d'outil. Un paramètre d'outil transite par le contexte du modèle et se retrouve conservé dans les transcripts de conversation. Ils sont donc lus uniquement depuis l'environnement du processus ou depuis le fichier écrit par login.
⚠️
ARA_AUTH_TOKENexpire au bout de 24 heures. Les jetons d'Ara sont signés avecexpiresIn: "24h": un jeton collé à la main cesse de fonctionner le lendemain. Ne l'utilisez que pour une intégration automatisée qui sait le renouveler. Pour un usage quotidien, préférezloginci-dessus, ou à défautARA_USERNAME/ARA_PASSWORD— qui suppose en revanche d'écrire un mot de passe en clair dans un fichier de configuration.
L'outil auth_refresh rejoue l'authentification en cours de session, si un jeton a expiré.
Outils
Chaque outil porte des annotations (readOnlyHint, destructiveHint, idempotentHint) qui permettent à votre client MCP de demander confirmation avant les opérations sensibles.
Outil | Nature | Description |
| 📖 référentiel | Plan de travail : quels critères exigent quoi |
| 📖 référentiel | Index des critères RGAA (numéro + intitulé), filtrable |
| 📖 référentiel | Un critère, ses tests et ce qu'il faut pour le vérifier |
| ↻ | Rejoue l'authentification depuis l'environnement |
| ✚ additif | Créer un nouvel audit |
| ✚ additif | Dupliquer un audit (la source n'est pas touchée) |
| 🔒 lecture seule | Récupérer un audit complet |
| 🔒 lecture seule | Avancement : ce qui reste à évaluer, par page |
| 🔒 lecture seule | Résultats de critères, filtrables par page et par statut |
| 🔒 lecture seule | Rapport complet avec taux de conformité |
| 🔒 lecture seule | Export CSV des résultats |
| ⚠️ destructif | Mise à jour complète — remplace les métadonnées |
| ⚠️ destructif | Remplace les notes de l'audit |
| ⚠️ destructif | Remplace l'évaluation des critères visés |
| ⚠️ destructif | Remplace ET publie la déclaration d'accessibilité |
| ⚠️ destructif | Rend l'audit public — irréversible (voir ci-dessous) |
| ⚠️ destructif | Suppression (410 ensuite) — ne dépublie pas |
Le référentiel RGAA embarqué
Le serveur embarque le référentiel RGAA 4.1 complet — 13 thématiques, 106 critères, et les tests de chacun. Sans lui, un agent ne manipule que des numéros (topic: 6, criterium: 1) sans savoir ce qu'il évalue.
list_rgaa_criteria(auditType: "FAST") → les 25 critères de l'audit rapide (~5 Ko)
get_rgaa_criterion(topic: 6, criterium: 1)
→ « Chaque lien est-il explicite (hors cas particuliers) ? » + ses 5 tests (~2 Ko)Le geste attendu pendant un audit : get_rgaa_criterion pour lire le critère et ses tests, puis update_audit_results pour poser le verdict. Juger plutôt que deviner.
Les données proviennent de rgaa.json du projet Ara, publié par la DINUM sous Licence Ouverte 2.0. Elles sont embarquées dans le paquet — le serveur fonctionne donc hors ligne, sans appel réseau pour la partie référentiel. Régénération : node scripts/build-rgaa-data.mjs.
À noter : les types d'audit
FASTetCOMPLEMENTARYcouvrent 25 critères chacun et sont disjoints ; c'est la méthodologie complète (rapide + complémentaire) qui en couvre 50.
Le code source ne suffit pas
Sur les 106 critères du RGAA, 40 seulement se tranchent en lisant le HTML — et 6 sur les 25 d'un audit rapide. Les autres exigent la page rendue, une navigation clavier réelle, l'arbre d'accessibilité, ou un jugement éditorial.
C'est le piège de l'audit assisté par IA : un agent lit du balisage, y trouve des réponses plausibles, et remplit un audit qui ne repose sur rien. Trois mécanismes s'y opposent.
get_audit_method(auditType) — le plan de travail avant de commencer : quels critères relèvent du source, du rendu, du clavier, de la restitution, du jugement.
get_rgaa_criterion joint à chaque critère un bloc verification : sourceSuffit, les besoins, et comment s'y prendre.
update_audit_results refuse un verdict non fondé. Déclarer CONFORME ou NON CONFORME sur un critère qui exige davantage, sans renseigner le champ evidence correspondant, produit une erreur explicite :
Verdict refusé sur 1 critère(s) : le code source ne suffit pas à les trancher,
et la vérification correspondante n'a pas été déclarée.
10.7 — exige : clavier (…) ; rendu (…)
Effectuez réellement ces vérifications, puis renseignez le champ "evidence".
Si vous ne pouvez pas les faire, utilisez le statut NOT_TESTED plutôt qu'un
verdict non fondé.NOT_TESTED et NOT_APPLICABLE en sont dispensés : ils n'affirment rien. Et evidence reste déclaratif — un agent peut mentir, mais plus par omission.
Cette classification est une guidance de ce serveur, déduite du vocabulaire des tests puis corrigée à la main. Le RGAA dit quoi vérifier, pas avec quel outil.
⚠️ Publier est irréversible
Ara n'offre aucune dépublication, et supprimer un audit ne retire pas son rapport publié :
Après | |
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Le rapport devient alors inaccessible depuis l'interface d'Ara : vous ne pouvez plus ni le consulter, ni le corriger, ni le retirer. Seul votre nom d'auditeur disparaît du rapport public ; le contenu de l'audit demeure.
Deux conséquences pratiques :
ne traitez jamais la suppression comme un moyen d'annuler une publication ;
publier un audit portant sur un site tiers met en ligne une déclaration d'accessibilité le concernant, signée de vous — assurez-vous d'en avoir le mandat.
Citer du HTML dans un commentaire
Ara affiche les commentaires de critère en texte riche : un <th> écrit tel quel est interprété comme une balise et disparaît du commentaire rendu — l'API répond 200, le constat perd sa substance, et rien ne le signale.
Depuis la 2.2.1, update_audit_results échappe < et > dans compliantComment, notApplicableComment et le title/comment de chaque notCompliantItems. Citez donc le balisage librement :
"comment": "Le champ n'a ni <label for>, ni aria-label."
↳ affiché dans Ara : Le champ n'a ni <label for>, ni aria-label.N'échappez pas vous-même : & est laissé intact, donc un <th> déjà échappé reste correct.
Exception : le champ notes (patch_audit_notes) reste du texte riche non échappé — c'est le champ prévu pour la mise en forme. Pour y citer du balisage, écrivez <th>.
Révisions de protocole MCP
Depuis la 2.1.0, le serveur sert les deux révisions de la spécification depuis le même code, en négociant à l'ouverture de la connexion :
2025-11-25— poignée de maininitialize, comme avant.2026-07-28— sans état : plus deinitialize,server/discover,resultType, et des indices de cache (ttlMs/cacheScope) sur le catalogue d'outils.
Il n'y a rien à configurer : votre client obtient la révision qu'il sait parler.
Migration depuis la 1.x
La 2.0 supprime l'outil auth_signin, qui recevait l'e-mail et le mot de passe en paramètres — donc à travers le contexte du modèle.
Retirez tout appel à
auth_signinde vos scripts ou prompts.Mettez vos identifiants dans le bloc
envde la configuration MCP (voir Authentification) : le serveur s'authentifie tout seul au démarrage.auth_refresh, sans argument, remplace le besoin d'une reconnexion manuelle en cours de session.
Corrigé au passage : signin envoyait l'en-tête Authorization avec le jeton courant, ce qui faisait répondre 404 Cannot POST /api/auth/signin à l'API dès que ce jeton était expiré — précisément le cas où l'on cherche à se reconnecter.
Workflow typique
1. get_audit_method("FULL") # De quoi aurai-je besoin ?
2. create_audit(FULL, "MonSite", pages...) # Créer l'audit (106 critères)
3. get_audit(editUniqueId) # Récupérer les IDs de page
4. get_rgaa_criterion(topic, criterium) # Lire le critère et ses tests
5. update_audit_results(...) # Poser le verdict, page par page
6. get_audit_progress(editUniqueId) # Que reste-t-il ?
↳ revenir en 4 tant qu'il reste des critères
7. update_statement(editUniqueId, ...) # Remplir la déclaration
8. publish_audit(editUniqueId) # Publier l'audit terminé
9. get_report(consultUniqueId) # Consulter le rapport finalL'audit complet est le cas normal : seul un audit sur les 106 critères fonde une déclaration d'accessibilité. FAST (25 critères) et COMPLEMENTARY (25 autres) servent à repérer, pas à déclarer.
Un audit complet, c'est 106 critères par page, éléments transverses compris — 318 résultats pour deux pages, près d'un millier sur un échantillon de huit. D'où la boucle 4→6 : évaluer par lots, puis demander ce qu'il reste avec get_audit_progress plutôt que de rapatrier tous les résultats.
L'authentification est faite au démarrage du serveur depuis l'environnement : aucune étape de login dans le workflow.
Enums RGAA
Types d'audit
FULL— 106 critères (audit complet)FAST— 25 critères (audit rapide)COMPLEMENTARY— 50 critères (audit complémentaire)
Statuts de critère
COMPLIANT— ConformeNOT_COMPLIANT— Non conformeNOT_APPLICABLE— Non applicableNOT_TESTED— Non testé
Impact utilisateur
MINOR— MineurMAJOR— MajeurBLOCKING— Bloquant
Thématiques RGAA (topics 1-13)
Images
Cadres
Couleurs
Multimédia
Tableaux
Liens
Scripts
Éléments obligatoires
Structuration de l'information
Présentation de l'information
Formulaires
Navigation
Consultation
Cartographie des routes Ara
Audits (/audits)
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Rapports (/reports) — lecture seule
Méthode | Route | Outil MCP |
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Authentification (/auth)
Méthode | Route | Outil MCP |
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Routes non exposées (hors périmètre MCP)
Route | Raison |
| Le |
| Upload d'image (deprecated) |
| Upload de fichier |
| Upload d'image éditeur |
| Suppression image |
| Suppression fichier |
| Liste d'audits (nécessite auth account) |
| Création de compte |
| Vérification de compte |
| Profil utilisateur |
| Retour utilisateur |
Développement
git clone https://github.com/DavidPivert/ara-rgaa-mcp.git
cd ara-rgaa-mcp
npm install
npm run build # compile vers build/
npm run typecheck # tsc --noEmitPour brancher la copie locale sur un client MCP, pointer command sur node et args sur le chemin absolu de build/index.js — ou utiliser run.sh, qui fait le cd nécessaire à la résolution des node_modules.
Licence
EUPL-1.2 — Licence Publique de l'Union Européenne, pour le code de ce dépôt.
Le référentiel RGAA embarqué (src/rgaa-data.ts) est extrait du projet Ara et reste sous Licence Ouverte 2.0 — Direction interministérielle du numérique (DINUM).
Ce serveur est un projet indépendant : il consomme l'API d'Ara sans en reprendre le code. Ara est publié par la DINUM sous licence MIT, qui n'impose aucune contrainte sur la licence de ce dépôt.
Available Tools
14 toolsauth_signinA
Authenticate to the Ara platform using email/password. Returns a JWT token that will be used for all subsequent requests. Required only if ARA_AUTH_TOKEN is not set.
| Name | Required | Description | Default |
|---|---|---|---|
| username | Yes | Your Ara account email | |
| password | Yes | Your Ara account password |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only mentions 'returns a JWT token' but lacks details on side effects, token format, expiration, error handling, or rate limiting. This is insufficient for a critical authentication tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, immediately stating the purpose and then the condition for use. Every sentence adds value, with no wasted words or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of an output schema, the description should elaborate on the return value (e.g., token format, how to use it) and mention potential errors or prerequisites. The current description leaves significant gaps, especially for a tool essential for subsequent requests.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters well-described in the schema ('Your Ara account email' and 'Your Ara account password'). The description adds no additional meaning beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool authenticates to the Ara platform using email/password and returns a JWT token. It distinguishes itself from sibling tools (all audit-related) by specifying its authentication purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear condition for use: 'Required only if ARA_AUTH_TOKEN is not set.' This gives context on when to invoke it. No explicit alternatives or when-not-to-use, but sibling tools are unrelated, so it's adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_auditA
Create a new RGAA accessibility audit in Ara. Returns the audit with its editUniqueId (for editing) and consultUniqueId (for viewing the report).
Audit types:
FULL: all 106 RGAA criteria
FAST: 25 key criteria (audit rapide)
COMPLEMENTARY: 50 criteria (audit complémentaire)
| Name | Required | Description | Default |
|---|---|---|---|
| auditType | Yes | Type of RGAA audit | |
| procedureName | Yes | Name of the audited procedure/site | |
| pages | Yes | List of pages to audit | |
| auditorName | Yes | Name of the auditor | |
| auditorEmail | No | Email of the auditor | |
| pageElements | Yes | Types of elements present on the site |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry behavioral info. It covers return values and audit types but omits side effects, permissions, or failure behavior. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two paragraphs, front-loaded with core purpose. Each sentence adds value. Could be more concise by merging lines, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 params, no output schema, and no annotations, the description covers return values and audit types. Schema already details params, so description is reasonably complete for a creation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. Description adds meaning for auditType (explains FULL, FAST, COMPLEMENTARY) and mentions IDs, but other params like procedureName and pages are not further explained beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a new RGAA accessibility audit and returns unique IDs. It distinguishes from sibling tools like update_audit or delete_audit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use guidance or alternatives. The description defines audit types but does not advise on when to use this tool versus others like duplicate_audit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_auditA
Soft-delete an audit. The audit will return HTTP 410 Gone for future requests.
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit to delete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the soft-delete behavior and HTTP 410 Gone response, but does not mention whether the deletion is reversible or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that immediately convey the action and the behavioral effect. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple deletion tool with one well-documented parameter and no output schema, the description adequately explains the operation and its HTTP response. However, it could mention the return value or recoverability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter, and the description adds no extra meaning beyond what is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Soft-delete' and the resource 'an audit', distinguishing it from other operations like create_audit or update_audit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use soft-delete versus alternatives, but the operation is straightforward. No exclusion criteria or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
duplicate_auditA
Fully duplicate an existing audit (metadata, pages, RGAA results, example images). Returns a new audit with fresh IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit to duplicate | |
| procedureName | Yes | Name for the duplicated audit |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries burden. States 'Fully duplicate' and 'Returns a new audit with fresh IDs,' indicating no modification to original, but omits permissions, rate limits, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, front-loaded with key action, zero waste. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 simple params and no output schema, description covers what is duplicated and returned. Could mention limitations or prerequisites, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The tool description adds no additional meaning beyond what the schema provides, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'duplicate', resource 'audit', and scope 'fully' plus listing components (metadata, pages, RGAA results, example images) clearly distinguish it from sibling tools like create_audit or delete_audit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies when to use (for duplicating an audit) but lacks explicit guidance on when not to use, prerequisites, or comparisons with sibling tools like create_audit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
export_csvB
Export audit results in CSV format.
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose whether export is synchronous, returns data directly, or triggers a download. Lacks details on file size limits or response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no redundancy; however, it could be slightly expanded to include output format without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Minimal description for a simple tool; lacks indication of output form (e.g., file download, URL) or error cases. No output schema to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'uniqueId', with description already provided in schema. Tool description adds no extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specifies verb 'Export' and resource 'audit results in CSV format', clearly distinguishing from sibling tools like get_audit or get_report.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like get_audit_results or get_report. No prerequisites or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_auditA
Retrieve a full audit by its editUniqueId. Returns all metadata, pages, environments, and notes.
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must inform behavior. It indicates a read-only retrieval but does not disclose permissions, side effects, or error conditions. Adequate for a simple read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence front-loads the action and parameter, then lists returned content. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one parameter, the description sufficiently explains what it does and what it returns. Missing an output schema but not required; still reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers the single parameter completely (100% coverage). Description adds no additional meaning beyond the schema, just restates the parameter's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a full audit by editUniqueId and lists the returned data (metadata, pages, environments, notes). It distinguishes from sibling tools like create_audit, delete_audit, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this versus alternatives. Usage is implied as a retrieval operation after creation, but no direct mention of context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_audit_resultsA
Retrieve all criterion results for an audit. Returns an array of results, each with:
topic (1-13): RGAA topic number
criterium: criterion number within the topic
pageId: ID of the audited page
status: COMPLIANT | NOT_COMPLIANT | NOT_APPLICABLE | NOT_TESTED
compliantComment / notCompliantComment / notApplicableComment
userImpact: MINOR | MAJOR | BLOCKING (when not compliant)
quickWin: whether the fix is easy
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states 'Retrieve' indicating read-only, but doesn't disclose authentication needs, rate limits, or potential performance implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is fairly concise and well-structured with bullet points for return fields. Could be slightly shorter, but effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Missing output schema is compensated by detailed field list. However, no guidance on when to use vs siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter with 100% schema coverage. Description explains output but adds no extra meaning for the uniqueId parameter beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses clear verb 'Retrieve' and specific resource 'criterion results for an audit'. It distinguishes from siblings like get_page_results by returning all results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when or when-not to use. Context from sibling tool names implies it's for full audit results, but no direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_page_resultsA
Get criterion results for a specific page of an audit. The pageSlug is typically the page order number.
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit | |
| pageSlug | Yes | The page slug (usually its order number) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It indicates a read operation but does not explicitly state it is read-only, nor does it mention pagination, limits, or side effects. Basic transparency is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, focused sentences with no redundancy. Every word adds value, and the description is front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (2 required params, no nested objects, no output schema), the description is adequate but lacks usage guidelines. It does not explain return values or pagination behavior, which could be expected for a paginated tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds minor context ('pageSlug is typically the page order number'), which largely repeats the schema description. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves criterion results for a specific page of an audit, using the verb 'get' and the resource 'criterion results for a page.' It distinguishes itself from sibling 'get_audit_results' by specifying the page scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'get_audit_results' or other siblings. The description does not specify context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_reportA
Get the full audit report (read-only). Includes accessibility rate, criteria counts, and result distributions by page and topic. Uses the consultUniqueId (not the editUniqueId).
| Name | Required | Description | Default |
|---|---|---|---|
| consultUniqueId | Yes | The consultUniqueId of the audit (found in the audit data) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It declares read-only behavior and describes what data is returned, but lacks details on authentication, rate limits, or performance constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three efficient sentences front-loaded with purpose and key details. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, read-only, no output schema), the description covers all necessary aspects: purpose, contents, parameter semantics, and safety.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by clarifying that the parameter is the consultUniqueId (not editUniqueId), which is critical for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves the full audit report as read-only, listing specific contents. The mention of using consultUniqueId distinguishes it from sibling tools that may use editUniqueId or have narrower scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It specifies using consultUniqueId instead of editUniqueId, which guides correct parameter usage. However, it does not explicitly state when to prefer this tool over siblings like get_audit or get_audit_results.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
patch_audit_notesA
Update only the notes field of an audit. Useful for adding audit observations without touching other metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit | |
| notes | Yes | New notes content (rich text / HTML) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It correctly states it only updates notes, but omits response structure, side effects, or auth requirements. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main action. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-param tool with no output schema, the description is sufficient. It covers purpose and usage guidance adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. Description adds that notes are 'rich text / HTML', extending the schema description. Good but not exceptional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it updates only the notes field of an audit, distinguishing it from update_audit. The verb 'Update only' and resource 'notes field of an audit' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'useful for adding audit observations without touching other metadata', which implies when to use. Does not name alternatives but siblings like update_audit provide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
publish_auditA
Mark an audit as published/completed. The audit must be fully filled in (all criteria evaluated) before publishing. Returns HTTP 409 if incomplete.
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit to publish |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description discloses a precondition and a specific error (409) but does not mention other behaviors like idempotency, side effects, or success response. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. Key information (action, precondition, error) is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple publish action with one parameter and no output schema, the description adequately covers purpose, precondition, and a key error. Missing success response, but acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameter description. Description adds minimal value by implying the 'uniqueId' is the audit identifier, but no new semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'publish' and resource 'audit', specifying it marks as published/completed. It distinguishes from sibling tools like create_audit and update_audit by indicating a completion action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly mentions precondition (audit must be fully filled in) and error response (HTTP 409 if incomplete), guiding when to use. Could elaborate on when not to use, but sufficiently clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_auditC
Full update of an audit's metadata (procedure info, auditor info, environments, tools, technologies, notes, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit | |
| auditType | Yes | ||
| procedureName | Yes | ||
| pages | Yes | ||
| auditorName | Yes | ||
| auditorEmail | No | ||
| procedureUrl | No | URL of the audited site | |
| initiator | No | Organisation requesting the audit | |
| auditorOrganisation | No | ||
| contactName | No | Accessibility contact name | |
| contactEmail | No | Accessibility contact email | |
| contactFormUrl | No | URL of accessibility contact form | |
| tools | No | Audit tools used (e.g. ['Axe', 'WAVE']) | |
| environments | No | Test environments used | |
| technologies | No | Technologies used on the site (e.g. ['HTML', 'CSS', 'JavaScript']) | |
| notCompliantContent | No | Description of non-compliant content | |
| derogatedContent | No | Description of derogated content | |
| notInScopeContent | No | Description of content not in scope | |
| notes | No | General audit notes (rich text) | |
| transverseElements | No | Transverse elements (e.g. ['En-tête', 'Pied de page']) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry burden. 'Full update' is ambiguous—it might imply a complete replacement of all metadata, but the input schema has many optional fields, suggesting partial updates. No info on side effects, auth needs, or data overwrite behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that front-loads the purpose and lists categories. Concise and to the point, though it could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 20 parameters and no annotations or output schema, the description is too brief. Missing details on return value, error conditions, required permissions, and whether the update is fully replacing or merging.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 70%, so the schema handles most parameter meaning. The description groups parameters into categories (procedure info, environments, etc.), adding some value but not deep semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'update' and the resource 'audit's metadata', and lists categories like procedure info, auditor info, etc. It is specific but does not differentiate from siblings like patch_audit_notes, though the 'full update' phrasing hints at scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. The sibling list includes patch_audit_notes for partial updates, but the description does not mention this or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_audit_resultsA
Update criterion results for an audit. Send an array of result items. Each item targets one criterion on one page using (pageId, topic, criterium).
The topic/criterium must be a valid RGAA combination. Topics 1-13:
Images, 2. Cadres, 3. Couleurs, 4. Multimédia, 5. Tableaux,
Liens, 7. Scripts, 8. Éléments obligatoires, 9. Structuration,
Présentation, 11. Formulaires, 12. Navigation, 13. Consultation
Status values: COMPLIANT, NOT_COMPLIANT, NOT_APPLICABLE, NOT_TESTED User impact values: MINOR, MAJOR, BLOCKING
| Name | Required | Description | Default |
|---|---|---|---|
| uniqueId | Yes | The editUniqueId of the audit | |
| results | Yes | Array of criterion results to update |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'update', implying mutation, but lacks details on idempotency, authorization requirements, or whether existing results are replaced or appended.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately long but well-structured: first sentence states purpose, then breaks down item structure and allowed values. It's efficient but could be slightly shorter without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description is adequate for understanding input requirements but lacks details on success/error responses, which are common for write operations. It should mention if results are fully replaced or merged.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with descriptions for each parameter. The description adds value by explaining the array structure, listing topic numbers with names, and enumerating status and user impact values, which are not fully captured in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool updates criterion results for an audit using an array of items. The verb 'update' and resource 'criterion results' are specific, and no sibling tool has a similar write function for results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides detailed allowed values (topics, statuses, user impacts) which guide parameter usage, but it doesn't explicitly compare with sibling tools like get_audit_results or state when to prefer this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_statementB
Update the accessibility statement (déclaration d'accessibilité) for an audit. This is used to generate the public accessibility statement.
| Name | Required | Description | Default |
|---|---|---|---|
| editUniqueId | Yes | The editUniqueId of the audit | |
| initiator | No | Organisation requesting the audit | |
| auditorOrganisation | No | Auditing organisation | |
| procedureUrl | No | URL of the audited site | |
| contactName | No | Accessibility contact name | |
| contactEmail | No | Accessibility contact email | |
| contactFormUrl | No | Accessibility contact form URL | |
| technologies | No | Technologies used | |
| tools | No | Audit tools used | |
| environments | No | Test environments | |
| notCompliantContent | No | ||
| derogatedContent | No | ||
| notInScopeContent | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the tool updates and generates a public statement, but does not disclose side effects, permissions, or whether it is idempotent or destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that are front-loaded with the core purpose, containing no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 13 input parameters and no output schema or annotations, the description is insufficient. It lacks guidance on expected behavior and how parameters interact, leaving the agent with a poor understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 77% (moderate), but the description adds no additional meaning to parameters. It does not explain how parameters map to the accessibility statement fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Update' and resource 'accessibility statement for an audit', and distinguishes from sibling tools like update_audit and update_audit_results by specifying it generates the public accessibility statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as update_audit. The description does not mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
14 tool updates
v1.0.0- First observed
auth_signin - First observed
create_audit - First observed
delete_audit - First observed
duplicate_audit - First observed
export_csv - First observed
get_audit - First observed
get_audit_results - First observed
get_page_results - First observed
get_report - First observed
patch_audit_notes - First observed
publish_audit - First observed
update_audit - First observed
update_audit_results - First observed
update_statement
TDQS
Scored across 14 tools
Each tool targets a distinct action within the audit lifecycle: authentication, CRUD for audits, result management, export, report generation, and statement updates. No two tools have overlapping purposes, and descriptions clearly differentiate them.
All tools follow a consistent verb_noun snake_case pattern (e.g., create_audit, get_audit_results, update_statement). 'auth_signin' is slightly different but still fits the pattern. No mixing of styles.
14 tools cover the full scope of RGAA audit management: authentication, full CRUD, duplicate, publish, export, and result updates. This is well-scoped for the domain without being excessive or insufficient.
The tool set covers all major operations (create, read, update, delete, duplicate, publish, export, statement). A minor gap is the lack of a 'list_audits' tool to retrieve all audits, but core workflows are well-supported.
Maintenance
Related MCP Connectors
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Accessibility pre-checks (WCAG/BFSG) in a real browser + statement drafts. Pay per call.
Governed MCP gateway: one endpoint for your tools, with credential custody and audit log.
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Your Aurentia workspace — projects, CRM, tasks, deliverables — in Claude, Cursor or any MCP client.
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