Audity for Agents

Drive your Audity workspace from any HTTP client, automation tool, or AI assistant.

What Audity is, briefly

Audity is a B2B SaaS platform for AI consultants. It runs structured audits of a client’s business, surfaces opportunities and risks via AI synthesis, manages an inbox of inbound leads from public ReadyLink surveys, and remembers everything across engagements via a layer called Nucleus.

If you’re a consultant inside the app, you upload documents, click “run audit,” review the output, ship deliverables. If you’re outside the app, you do the same things from your AI assistant.

This site documents the agent API, the surface that lets external AI agents act on a consultant’s Audity workspace.

What the agent API is for

Three concrete outcomes a consultant gets when they wire an AI agent up to Audity:

1. Run an audit without leaving your chat window. “Start an Audity project for , , . Run the analysis. Summarize the top three opportunities.” Three real API calls, one prompt, one paragraph back.
2. Triage your lead inbox in 30 seconds. “Pull my Audity leads from this week scored above 70. Convert the top three into projects. Trigger analysis on each.” A workflow that used to be 15 minutes of dashboard clicking, done from Claude Desktop.
3. Query your accumulated client knowledge from anywhere. “What do I remember about Acme’s stakeholder concerns? Are there patterns I’ve seen across other healthcare clients?” Nucleus, your persistent memory layer, becomes searchable from any AI assistant.

If those sound useful, start with the API Quickstart (curl) if you want direct REST access, or the Agent Quickstart if you’re wiring up Claude, ChatGPT, or Cursor. If you want to know what’s under the hood first, keep reading.

How it works

┌──────────────────────────────────────────────────────────────────┐
│  Your code, agent, or automation (curl, Python, n8n, Zapier...)  │
└────────────────────────┬─────────────────────────────────────────┘
                         │ HTTPS + Bearer PAT
                         ▼
┌──────────────────────────────────────────────────────────────────┐
│  Audity REST API (app.auditynow.com)                             │
│  OpenAPI 3.1, every endpoint documented in the API Reference    │
└────────────────────────┬─────────────────────────────────────────┘
                         │
                         │ PAT resolves to your Clerk identity
                         │ → tier + RLS gates apply
                         ▼
┌──────────────────────────────────────────────────────────────────┐
│  Your workspace data: projects, Nucleus, leads, contacts         │
└──────────────────────────────────────────────────────────────────┘

Every agent call goes through the same permission stack that protects the web app:

• Your PAT proves you are you (issued from your settings page; bcrypt-hashed at rest)
• Your subscription tier gates which features are callable
• Supabase Row-Level Security ensures the agent only sees data you own
• Credit deductions apply normally, creating a project costs credits whether it’s clicked from the dashboard or invoked from Claude

Ways to use the API

Direct HTTP (scripts, automations, custom integrations). Call any endpoint with Authorization: Bearer aky_... from curl, Python, JavaScript, n8n HTTP nodes, Zapier, Make, or any HTTP client. The full spec is at /api-reference/openapi.json and there’s a complete curl walkthrough at API Quickstart.

Through an AI agent connector (Claude Desktop, claude.ai, ChatGPT, Cursor). If you want an AI assistant to call Audity on your behalf during a conversation, use the MCP server at docs.auditynow.com/mcp. Drop that URL into your agent’s settings with your PAT and every endpoint becomes a callable tool. See Connect Your Agent.

Claude Code. Claude Code has native MCP support via a 3-line JSON config file — no GUI, no OAuth — giving you the Audity operations as typed tools with full schema validation. If you need zero external dependencies, there’s a CLAUDE.md fallback where Claude makes direct REST calls instead (no typed schemas). See Claude Code guide.

What you can do today

Capability	Endpoints
List, fetch, create, and patch projects	GET/POST /api/projects, GET/PATCH /api/projects/{id}
Trigger audit synthesis (the AI pipeline)	POST /api/projects/{id}/audit-analysis, POST /api/agent/projects/{id}/audit-analysis/async
Read AI-generated opportunities and full deliverables	GET .../opportunities, GET .../deliverables
List leads from your ReadyLinks and convert them	GET /api/lead-generation/leads, POST .../convert
Manage ReadyLinks and assessment templates	GET/POST/PATCH/DELETE /api/agent/readylinks, GET/POST/PATCH/DELETE /api/agent/assessment-configs
Search and create Nucleus memories	GET /api/nucleus/memories, POST /api/nucleus/memories
Submit text captures (transcripts, notes) and read extracted items	POST /api/nucleus/capture/note, GET /api/nucleus/captures/{id}
Read proactive insights generated by background jobs	GET /api/nucleus/insights
Manage the lightweight contact CRM	GET/POST/PATCH/DELETE /api/nucleus/contacts
Check your tier, credits, and current identity	GET /api/user/{current,tier,credits}

The full path list and request/response shapes are in the API Reference.

The async audit endpoint is for projects that already have current document and interview analyses. For a brand-new project, use the synchronous audit endpoint first and verify status before retrying if your client times out.

What’s intentionally out of scope for v1

The agent surface is deliberately narrow. These belong to the web app, not the API:

• Document upload. PDFs, transcripts, contracts go through the web app. Once uploaded, agents can read them via project detail and trigger analysis.
• Streaming responses. Audity returns structured JSON, not chat tokens. Stream prose with your own LLM; use Audity for synthesis, memory, project state.
• Deliverable document regeneration. The synthesis pipeline produces stakeholder memos and other deliverable docs once audit-analysis runs. Agents read them, they don’t trigger fresh generation in v1.
• Web research. The route exists but isn’t agent-accessible in v1. Run it from the dashboard.
• PAT management via PAT. Tokens are created and revoked from a browser session, not via the API itself.

If a workflow you need crosses one of these lines, tell us.

Start here

API Quickstart (curl)

Verify your token and run a real audit end to end from a terminal. No agent required.

Authentication

Token format, scopes, rotation, error codes, and what gets logged.

Claude Desktop / claude.ai

Add Audity as a connector inside Claude Desktop or claude.ai (MCP).

Claude Code

MCP via a 3-line JSON config, or call the REST API directly via CLAUDE.md.

ChatGPT

Wire Audity into a Custom GPT via OpenAPI Actions.

Cursor

Drop the MCP server into Cursor’s tool palette.

n8n

Use the MCP Client node, or call endpoints from HTTP Request nodes.

What’s under the hood

If you’re building an integration:

• The full API is documented as OpenAPI 3.1 at /api-reference/openapi.json
• The MCP server is auto-generated from the OpenAPI spec, when we add an endpoint, it’s available as a new MCP tool on the next docs deploy
• Auth is Bearer token (aky_<32 chars>) issued from your Audity settings page
• The token resolver runs in middleware; tier and RLS enforcement happens in route handlers
• Last verified against the public OpenAPI spec: May 5, 2026.

Ready? Start with the quickstart →