MCP & API access
Audity has an API and an MCP server
Built for agent-native consultants. Audity Pro plugs straight into Claude Code, Codex, Cursor or your own agent harness, so your agents can run the whole platform from the command line: intakes, assessments, analysis, ROI and deliverables. Paste one line to connect, then just ask in plain English. No code required. Prefer to build against it directly? It is a full REST API and MCP server under the hood.
Who this is for
This page is for you if: This is for consultants on Audity Pro (or a firm plan) who want to drive their discovery from the AI tools they already use: connect once, then ask your agent to handle intake, kick off analyses, and pull deliverables for you. No developer required, though the full API is there if you want it.
Building a product instead? Building a product, app, or platform and want to embed Audity for your own users? That's an integration partnership, not a subscription. See integration partnerships →
“I don't buy software unless my agents can connect to it.”
Built for consultants who already run on agents
We built Audity to that rule. If your agents already handle your follow-ups, research and delivery, they can run your discoveries in Audity too.
Run the whole platform from your harness
Everything you can do in the app, your agents can do from the command line or your agent harness. Tell one to chase a client for documents, run the analysis once they arrive, and ping you when it is ready for your call.
Pull all the data down
All raw data and all output data is stored. Your agents can pull every piece of it over MCP and build deliverables your own way, in your own format, with the tools and process you already use.
Have your agent check the platform's work
So you can sleep at night knowing there are no hallucinations: have your agent check the platform's work. The raw inputs and the outputs are both stored, so it can check every finding against the source before anything reaches your client.
Webhooks for the rest of your stack
A native GoHighLevel integration, plus Zapier, Make and n8n through webhooks. Add as many as you need, triggered on platform activity, on every plan. Example: start a follow-up when a prospect begins an assessment and doesn't finish it. Their progress saves on its own.
Choose your model provider
In settings, keep the system default or pick Anthropic, OpenAI or Google. Deep analysis runs on your provider's current frontier model, and document ingestion runs on a mid-tier model.
Your own trained model stays outside
Plugging your own trained model or second brain into the platform isn't supported. To use your own agents, go the other direction: Audity runs the discovery, then your agents pull the raw and output data out over MCP and process it however you work.
What you can do
What you can do over the API
Projects & intakes
List and manage projects, then create or prefill the business-context intake (business overview, strategic and operational context, pain points, engagement scope) so discovery starts from data you already hold.
Assessments & questionnaires
Build assessment templates, add custom questions, and generate per-stakeholder questionnaires. Read lead survey responses and AI readiness scores back as structured data.
Stakeholders & interviews
Add stakeholders, create interview sessions, and pull a unified interviewee view per project. Feed transcripts, voice notes, or emails in as captures and let Audity process them.
Analysis & opportunities
Kick off document and interview analysis jobs. Read the resulting opportunities, add or edit them, and select which ones flow through to ROI and deliverables.
ROI & deliverables
Create and update ROI calculations with computed scenarios and compile the final report: the same outputs the app produces, available to your stack.
Leads, ReadyLinks & CRM
List and update leads, convert a lead into a project, manage your ReadyLinks, and keep your lightweight contact CRM in sync: no dashboard required.
Model Context ProtocolIncluded with Audity Pro
How the MCP server works
The Model Context Protocol (MCP) server exposes Audity's actions as tools an AI agent can call directly, no glue code. Connect Claude, Cursor, or your own agent and it can run the discovery workflow the same way you would.
Start a new discovery for Acme Corp, mid-market, healthcare.
Run the analysis and summarize the top three opportunities.
1. Establish a data-ownership model (highest impact)
2. Stand up ML-ops capability in-house
3. Formalize model-risk governance
Run the analysis for the Initech project and email me the top three opportunities
Plain English in, discovery-grade results out
The same projects, analyses, and deliverables your team manages in the Audity app, driven in the words you already use. Nothing to script unless you want to.
Also available in
Connect once.
Drive everything.
One linePaste one line to connect, and everything the platform does becomes something you can ask for in plain English. Part of Audity Pro, not an add-on.
How to set it up
Set it up in three steps
01
Be on Audity Pro
Programmatic access comes with Audity Pro and firm plans, with no add-on or separate contract. Scout does not include it; you can upgrade inside the app if and when it fits.
02
Create a token
Generate a personal access token in your Audity settings. Use it as a bearer token to connect your MCP client or point your scripts at the API.
03
Run your discovery
Wire Audity into your tools or hand it to an agent. Run intakes, analyses, and deliverables on your own terms.
Programmatic access comes with Audity Pro
No add-on, no separate contract. The developer docs have the full endpoint reference, MCP setup, and a quickstart.