TaxAssist

An autonomous, multi-user Indian Income Tax filing assistant (ITR-1 & ITR-2) powered by Gemini on Google Cloud Agent Builder, with MongoDB (via the official MongoDB MCP server) as the data layer.

The agent reads a taxpayer's documents from Google Drive, extracts the figures with Gemini vision OCR, asks the user to confirm over email (human-in-the-loop), computes tax deterministically from official slab rates, writes the results back to Google Sheets, and exports a portal-ready ITR JSON (validated against the official Income Tax Department schema) — all under a strict, security-first architecture where the AI is treated as untrusted and can never tamper with tax data or leak personal information.

Architecture details: see SYSTEM_ARCHITECTURE.md.

Links

• Live app: https://taxassist-267786664719.asia-south1.run.app/
• Demo video (≤3 min):
• Partner track: MongoDB — via the official MongoDB MCP server (see MongoDB MCP integration).
• License: Apache-2.0 — also set in the GitHub repo's About sidebar.

Team

• Your Name — role
• Teammate — role

Try it live (no sign-in)

On the login screen, click “Try the live demo — no sign-in.” It starts an isolated demo tenant and runs the real agent — Drive → figures → deterministic compute → Google Sheet → Calendar reminder — on a sandbox Google Workspace, so judges experience the full integration without a Google consent screen.

How it works: the visitor is signed in with the app’s own session (no Google OAuth). A demo user holds no per-user token, so every Google call falls back to the team’s pre-authorized token.json (the sandbox account). Each visitor is a separate tenant; the email approval gate is auto-approved in demo mode (no reply inbox).

To enable it on a deployment, set DEMO_MODE=1 (+ optional DEMO_INBOX_EMAIL for the sandbox Gmail, DEMO_USER_DOMAIN) and mount the sandbox account’s token.json via GOOGLE_TOKEN_FILE. Share the sandbox Drive/Sheet publicly (view) so the in-app “Open results sheet / Drive folder” links work for anyone.

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What it does

• Drive → OCR: detects documents (Form 16, etc.), converts to PDF, extracts figures with Gemini 2.5-flash vision (handles dense tables and scans).
• Human-in-the-loop over email: emails the user to confirm extracted values / approve computation; reads the replies and resumes — as durable, resumable runs.
• Deterministic tax engine: ITR-1 & ITR-2 computed from official slab rates (no LLM in the math), old vs new regime comparison, with section 87A rebate and new-regime marginal relief. All rates live in a single source of truth (app/core/tax_rules.json) that the calculators and the agent's retrieve_tax_rules_tool both read — so they can never diverge.
• Google Workspace: Gmail, Calendar (deadline reminders), Sheets (findings + result), Drive — per user.
• Portal-ready ITR JSON: exports the computed return as the official Income Tax Department offline-utility JSON (ITR-1 & ITR-2), validated against the published schema (app/core/itr_json_export.py). Downloadable from the workspace once every task is verified.
• One-click live demo: judges run the real agent on a sandbox Google Workspace with no Google sign-in (see Try it live above).
• Multi-tenant: one account → many profiles (e.g. self + spouse), each isolated.

Scope: TaxAssist prepares a file-ready return — it extracts, verifies, computes, writes the results to your Google Sheet, and exports the official offline-utility JSON ready to upload. It does not auto-submit to the income-tax portal; the final upload + e-verification stay with you. Surcharge above ₹50L and the granular ITR-2 input schedules (per-transaction capital gains, foreign assets) are not yet itemised — the Part B totals are.

Tech stack

Layer	Tech
Agent	Gemini (2.0/2.5-flash) via Google ADK → Vertex AI Agent Engine
Data plane	MongoDB Atlas via the MongoDB MCP server (partner)
Control plane	PostgreSQL (users, profiles, encrypted tokens, feedback)
Queue	Redis + RQ (async runs)
API	FastAPI
OCR	Gemini vision + pdfplumber
Export	Official IT-Dept ITR JSON schema, validated via jsonschema

No competing AI or cloud services are used.

Security highlights

• 3-way handshake gateway (HMAC identity + state-gated authorization + intent reconciliation + payload sanitization; optional signed-request mode).
• PII vault — personal data is tokenized before the AI ever sees it; reconstructed only in the local layer for outbound writes.
• In-process guards — the agent cannot escalate the workflow or write fabricated tax data (provenance-checked); document registration is system-only.
• Strict email format — internal field keys / code never appear in emails (see app/core/email_format.py).
• Tenant isolation — every data access is validated against profile ownership.

Setup

1. Install: pip install -r requirements.txt
2. Env: copy .env.example → .env and fill it (generation commands are in the file). Minimum to boot: MONGO_URI, GOOGLE_API_KEY, AGENT_SECRET_KEY, CONTROL_ENC_KEY (+ POSTGRES_URL for the control plane; omit for SQLite dev).
3. Google OAuth: place credentials.json at the root (or set GOOGLE_CREDENTIALS_FILE). Production uses per-user web OAuth with tokens encrypted in Postgres.
4. MongoDB MCP server (optional locally; required for partner integration at runtime):

   export MDB_MCP_CONNECTION_STRING="$MONGO_URI"
   npx -y mongodb-mcp-server --transport http --httpPort 3000
   # then set MONGODB_MCP_URL=http://127.0.0.1:3000/mcp in .env
   

Run (local)

uvicorn app.main:app --reload                 # API + gateway
rq worker -u $REDIS_URL tax-agent             # async run worker (if REDIS_URL set)

Test

pytest app/tests -q

195 tests — unit/, integration/, security/ — all MongoDB & Google calls mocked (hermetic). Includes official-schema validation of the exported ITR JSON (both forms) and a full end-to-end live-demo workflow test (login → run → export). Tool-contract gate: python scripts/check_tool_schema.py.

Deploy

• Agent → Vertex AI Agent Engine: python -m app.orchestrator.agent_engine (set GOOGLE_CLOUD_PROJECT, GOOGLE_CLOUD_LOCATION, AGENT_ENGINE_STAGING_BUCKET).

• Backend → Docker (Dockerfile) → Google Cloud Run (app + mongodb-mcp/ service).

• CI/CD → .github/workflows/ci.yml: PRs run lint + tool-schema gate + tests; main → staging; release/dispatch → production (manual approval).

  Hosted url

  link

  Team Members

  • Harish Rajagopalan
  • Nihal Mouni
  • K Vikas

License

Apache-2.0.