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wealthi-coach-mcp-server

wealthi-coach-mcp-server

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by wealthi-ai

wealthi-coach-mcp-server

Read-only MCP server giving Wealthi's AI Coach scoped access to student progress data, without the AI ever touching Firestore or Supabase directly.

Why this exists

Before this server, two clients wrote and read student data directly via SDK calls: the dashboard against Supabase, the mobile app against Firestore. Any AI feature built on top of that would need direct database credentials — which violates Wealthi's own AI philosophy ("AI should never receive unrestricted database access," "AI should not expose internal system data"). This server is the single, narrow, auditable path by which AI systems read student data. It does not replace the app's existing read/write paths for UI rendering; it exists specifically for AI consumption.

Related MCP server: OfficeRnD MCP Server

Domain ownership

Domain

System of record

Read by

XP, streak, points, level

Firestore (users/{uid})

get_student_progress, get_coach_context

Quiz attempts

Firestore (users/{uid}/quizAttempts)

get_assessment_results, get_curriculum_progress

Achievements

Firestore (users/{uid}/achievements)

(reserved — not yet exposed; see Future Work)

Identity, grade band, parent link

Supabase profiles (project qsawrfybwwpgajefndnk)

get_student_profile, get_coach_context

Coach seen-content tracker

Supabase profiles.routing_signals

get_learning_signals, get_coach_context

This split is intentional and permanent, not a migration waypoint. See project history for the full reasoning — short version: Firestore owns event-heavy gamification data because that's already its strength and mobile's home turf; Supabase owns identity/relational data because it needs joins and row-level security that Firestore doesn't offer.

Known infrastructure note: as of 2026-06, qsawrfybwwpgajefndnk is the confirmed-correct Supabase project — verified directly against wealthihome/.env's VITE_SUPABASE_URL, which is what the live app actually uses. Wealthi has had multiple Supabase projects connected to the same Lovable workspace with no "active" indicator in Lovable's panel itself, so don't trust Lovable's panel alone to determine which project is correct — always cross-check against the app's actual env var.

Read-only scope (by design, not just by convention)

This server never writes to Firestore or Supabase. All six tools carry readOnlyHint: true / destructiveHint: false annotations, and the service layer (src/services/) contains no write methods at all — there's no update, set, or delete call anywhere in this codebase. Writes continue to go through existing paths:

  • Mobile's direct Firestore SDK writes (XP, streak, quiz submission)

  • Dashboard's existing Supabase writes (profile updates, routing_signals)

  • The dormancy-decay Edge Function (Supabase) for pattern-state decay

If a future use case needs the AI to act (e.g., "mark this content as seen" instead of just reading seen-content), that should be a deliberately designed, narrowly-scoped write tool added later with its own review — not an extension of this server's existing read tools, and not a broadening of its current credentials to writable ones.

Authentication & Credential Scoping

This server uses two separate, dedicated credentials, neither reused from any other Wealthi service. This matters because of a prior credential exposure incident — the fix isn't just rotating one key, it's making sure no future leak from this server compromises anything beyond what this server itself can read.

Firebase Admin (Firestore access)

  1. In the Firebase console for the project backing the mobile app, go to Project Settings → Service Accounts.

  2. Create a new service account specifically for this server — do not reuse the mobile app's or NestJS API's existing service account.

  3. Grant it the Cloud Datastore Viewer IAM role (Google Cloud Console → IAM, not the Firebase console) — this is a read-only role scoped to Firestore/Datastore. Firestore has no separate "read-only Admin SDK mode"; the restriction must be enforced at the IAM role level. Do not grant roles/datastore.user or roles/owner — both include write access.

  4. Generate a private key (JSON) for this service account and populate FIREBASE_PROJECT_ID, FIREBASE_CLIENT_EMAIL, FIREBASE_PRIVATE_KEY in .env from its contents.

  5. Store the JSON file itself in a secrets manager (not in this repo, not in plain .env in any deployed environment) — inject the three env vars at deploy time instead.

Supabase (identity + routing_signals access)

  1. In the Supabase dashboard for project qsawrfybwwpgajefndnk, go to Authentication → Policies and confirm profiles has row-level security enabled (it should already, given existing app usage).

  2. Create a dedicated Postgres role or use Supabase's API key management to issue a key scoped to read-only SELECT on profiles only — not the service_role key used by the existing Edge Functions. If Supabase's built-in key types don't offer this granularity directly, create a custom Postgres role with GRANT SELECT ON profiles TO wealthi_coach_readonly; and authenticate via that role's credentials, rather than defaulting to service_role.

  3. Populate SUPABASE_URL and SUPABASE_COACH_READONLY_KEY in .env.

Rotation discipline

Given the prior exposure incident: rotate both credentials on a fixed schedule (recommend quarterly), and immediately if this repo's CI/CD config, deployment logs, or any environment dump is ever suspected compromised. Because credentials are scoped narrowly and not shared with any other service, rotating them only requires redeploying this server — no coordination needed with the mobile app, dashboard, or NestJS API.

Repo location

This server lives in its own repo (wealthi-coach-mcp-server), separate from wealthi-ai/wealthihome (dashboard) and the mobile app's repo. It is not the "Wealthi Intelligence" Supabase project (a separate, unrelated leads-generation database) — that naming collision was identified and deliberately avoided when naming this repo. If "Wealthi Intelligence" or "Wealthi System" comes up in conversation, confirm which of (a) this repo, (b) the leads-gen Supabase project, or (c) the qsawrfybwwpgajefndnk Supabase project is actually meant — they are three different things that have been confused before.

Project structure

wealthi-coach-mcp-server/
├── package.json
├── tsconfig.json
├── .env.example
├── src/
│   ├── index.ts                      # entry point, transport selection
│   ├── types.ts                      # Coach-facing domain shapes
│   ├── constants.ts                  # collection/table names, limits
│   ├── tools/                        # MCP tool contracts (thin)
│   │   ├── getStudentProfile.ts
│   │   ├── getStudentProgress.ts
│   │   ├── getAssessmentResults.ts
│   │   ├── getCurriculumProgress.ts
│   │   ├── getLearningSignals.ts
│   │   └── getCoachContext.ts
│   ├── services/                     # DB clients + query/composition logic
│   │   ├── firebaseClient.ts
│   │   ├── supabaseClient.ts
│   │   ├── firestoreProgressService.ts
│   │   ├── supabaseProfileService.ts
│   │   ├── curriculumService.ts
│   │   └── learningSignalsService.ts
│   └── schemas/
│       └── studentInput.ts           # shared Zod input schemas
└── dist/                             # build output (gitignored)

Setup

npm install
cp .env.example .env   # fill in real credentials, see above
npm run build
npm start               # stdio mode by default

For HTTP mode (remote deployment):

TRANSPORT=http PORT=3000 npm start

Test with the MCP Inspector:

npm run inspect

How the AI Coach client calls this server

The AI Coach currently runs as a feature inside the dashboard (AICoachCard, coachContent.ts). To call this server from that context, add it as an MCP server in the Claude API request the Coach feature already makes:

const response = await fetch("https://api.anthropic.com/v1/messages", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    model: "claude-sonnet-4-6",
    max_tokens: 1000,
    messages: [
      {
        role: "user",
        content: "Open a Coach session for this student and recommend what to show next."
      }
    ],
    mcp_servers: [
      {
        type: "url",
        url: "https://<your-deployed-host>/mcp",
        name: "wealthi-coach-mcp-server"
      }
    ]
  })
});

In practice, the Coach prompt should instruct the model to call get_coach_context first, with the current student's ID, before generating any response — that's the single round-trip that gives it profile, progress, learning signals, and curriculum state together. The finer-grained tools (get_student_profile, get_student_progress, etc.) exist for cases where only one piece is needed, or for debugging which specific data source is returning unexpected values.

The student ID passed to these tools should come from the authenticated session on the dashboard/mobile side, never from anything the AI itself infers or that a user can supply via chat — that's what keeps this a properly scoped, per-student tool rather than an open query surface.

Future work (not built yet)

  • getAssessmentResults-style achievement tool (Firestore achievements collection is in the domain table but not yet exposed as a tool — add when Coach actually needs to reference specific achievements).

  • Teacher/School platform tools, once those surfaces exist — they belong in this same tools/+services/ structure, not a separate server.

  • If dormancy-decay and other currently-dormant Edge Functions get reactivated (see open infra note: they're pointed at a different Supabase project, jatohkwzfdoxzevnxrfl, than the live app uses, and have 0 invocations to date), get_learning_signals's momentum derivation may want to read their output directly instead of recomputing a simpler heuristic here.

Available Tools

6 tools
get_assessment_resultsGet Assessment ResultsA
Read-onlyIdempotent

Retrieve a student's recent quiz/assessment attempts, most recent first.

Reads from Firestore (users/{studentId}/quizAttempts). Paginated since this collection grows unbounded over a student's tenure — always check has_more.

Args:

  • student_id (string): The student's unique identifier.

  • limit (number): Max results to return, 1-50 (default 20).

  • cursor (string, optional): Pagination cursor from a previous call's next_cursor.

Returns: JSON object with schema: { "studentId": string, "results": [ { "attemptId": string, "topic": string, "score": number, // 0-100 "completedAt": string, // ISO 8601 "attemptNumber": number } ], "hasMore": boolean, "nextCursor": string // present only if hasMore is true }

Examples:

  • Use when: "How did this student do on their last few quizzes?" -> default limit

  • Use when: "Show me everything" -> paginate using next_cursor until has_more is false

Error Handling:

  • Returns an empty results array (not an error) if the student has no attempts yet.

Inputs: student_id (required), limit, cursor.

get_coach_contextGet Coach ContextA
Read-onlyIdempotent

Retrieve everything Coach needs to open a session with a student, in one call.

This is the primary entry point for AI Coach sessions — composes profile, progress, learning signals, and curriculum progress into a single object, so the Coach client doesn't need to know that two separate databases (Firestore and Supabase) are involved. Use the individual tools (get_student_profile, get_student_progress, get_learning_signals, get_curriculum_progress) only when you need just one piece, or for debugging a specific data source.

Args:

  • student_id (string): The student's unique identifier.

Returns: JSON object with schema: { "profile": { studentId, displayName, gradeBand, hasLinkedParent, enrolledAt }, "progress": { studentId, xp, level, streakCount, streakStatus, pointsBalance }, "signals": { studentId, momentumState, seenContentIds, daysSinceLastSession, recommendedInteractionType }, "curriculum": { studentId, topics: [...] } }

Examples:

  • Use when: "Start a Coach session for this student" -> call this first, every time, before generating any Coach response

  • Don't use when: you only need one field (e.g. just streak count) and want to minimize Firestore/Supabase reads -> use the specific tool instead

Error Handling:

  • Returns "Student not found" if get_student_profile finds no record. Progress/signals/curriculum default to safe empty states for new students who have a profile but haven't started any activity yet.

Inputs: student_id (required).

get_curriculum_progressGet Curriculum ProgressA
Read-onlyIdempotent

Retrieve a student's completion status across Wealthi's financial literacy topics (saving, budgeting, tradeoffs, delayed gratification, goal setting, decision making, financial confidence, future thinking, credit basics).

Derives completion from passing quiz attempts (score >= 70) grouped by topic and module, mapped against the same topic taxonomy used by Coach's content library (coachContent.ts) — so results align with what's shown in-app.

Args:

  • student_id (string): The student's unique identifier.

Returns: JSON object with schema: { "studentId": string, "topics": [ { "topicId": string, "topicLabel": string, "status": "not_started" | "in_progress" | "completed", "completedModules": number, "totalModules": number } ] }

Error Handling:

  • Always returns all 9 topics, even if the student hasn't started any (status will be "not_started" with completedModules: 0).

Inputs: student_id (required).

get_learning_signalsGet Learning SignalsA
Read-onlyIdempotent

Retrieve behavioral signals that inform what Coach should show a student next.

Composes data from two sources: Supabase (profiles.routing_signals, for already-seen content) and Firestore (last activity timestamp, for momentum). Returns translated behavioral labels only — never raw dormancy-decay scores or internal routing fields. This mirrors the translation Coach already does internally via behaviorLabels.ts.

Args:

  • student_id (string): The student's unique identifier.

Returns: JSON object with schema: { "studentId": string, "momentumState": "building" | "steady" | "dormant" | "returning", "seenContentIds": string[], // content already shown, for dedup "daysSinceLastSession": number, "recommendedInteractionType": "read" | "decide" | "reflect" }

Examples:

  • Use when: "What should Coach show this student right now?" -> check recommendedInteractionType and filter coachContent.ts by seenContentIds

  • Use when: deciding whether to show comeback/re-engagement copy -> check momentumState === "returning"

Error Handling:

  • A student with no activity history returns momentumState: "dormant" and daysSinceLastSession: 999 (sentinel for "never active"), not an error.

Inputs: student_id (required).

get_student_profileGet Student ProfileA
Read-onlyIdempotent

Retrieve a student's basic identity and enrollment information.

This tool does NOT return parent contact details, raw assessment data, or any internal scoring/routing fields — only what's needed to personalize Coach's tone and respect age-appropriate framing.

Args:

  • student_id (string): The student's unique identifier.

Returns: JSON object with schema: { "studentId": string, "displayName": string, // safe display name only "gradeBand": "elementary" | "middle" | "high" | "young_adult", "hasLinkedParent": boolean, // presence only, never parent identity "enrolledAt": string // ISO 8601 date }

Error Handling:

  • Returns "Student not found" if no profile exists for the given student_id.

Inputs: student_id (required).

get_student_progressGet Student ProgressA
Read-onlyIdempotent

Retrieve a student's current XP, level, streak, and points balance.

Reads from Firestore (users/{studentId}), which is the system of record for gamification/progress data. Does NOT include quiz-level detail — use get_assessment_results for that.

Args:

  • student_id (string): The student's unique identifier.

Returns: JSON object with schema: { "studentId": string, "xp": number, "level": number, "streakCount": number, "streakStatus": "active" | "at_risk" | "broken", "pointsBalance": number }

Error Handling:

  • Returns "Student not found" if no Firestore user document exists for student_id.

Inputs: student_id (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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    TDQS

    A4.5/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool serves a distinct function: assessment results, composite coach context, curriculum progress, learning signals, student profile, and student progress. No overlap in purpose; descriptions clearly differentiate them.

    Naming Consistency5/5

    All tools follow the 'get_' prefix with descriptive noun phrases (e.g., get_student_profile, get_learning_signals). The naming pattern is perfectly consistent.

    Tool Count5/5

    Six tools cover the essential data retrieval needs for an AI coach session: profile, progress, curriculum, learning signals, assessment results, and a composite tool. This is a well-scoped set that doesn't feel too few or too many.

    Completeness5/5

    The tools provide comprehensive coverage of student data: identity, progress metrics, curriculum status, behavioral signals, and quiz results. The composite tool (get_coach_context) further enhances completeness by bundling the most commonly needed data in one call. No obvious gaps for the stated coaching purpose.

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