MCP Server | QFlow Systems

The Governance Gap

Most organizations can’t safely connect AI to the information that matters most

AI assistants have moved quickly from experiment to expectation. But the information that drives real decisions — contracts, case files, approvals, official records — sits inside governed systems for good reason. Until now, connecting AI to that information meant choosing between usefulness and control.

AI can’t reach your trusted information

General-purpose AI assistants are fluent but uninformed. Without access to authoritative enterprise content, they work from public data or whatever an employee pastes into a chat window — producing answers that can’t be traced, verified, or defended.

AI operates outside your governance framework

Access controls, retention schedules, approval chains, and audit trails took years to establish. Most AI integrations sit beside those controls rather than inside them — creating a parallel path to sensitive information that governance teams cannot see or evidence.

Automation shouldn’t mean loss of control

Leaders are asked to deliver AI-driven efficiency and to prove nothing improper happened. When an AI assistant touches a case or a record, someone has to be able to answer: who authorized it, under what rule, and where is the evidence?

Use Cases

What your teams can actually do with it

Everyday requests, asked in plain language, carried out inside your governance framework.

Use case

What a user might ask

Business outcome

Clear an approval backlog

They ask“Walk my inbox, show me what’s routine, and complete the approvals that meet our standard criteria.”

OutcomeQueues that used to consume a morning are cleared in minutes — each action recorded under the approver’s own identity.

Find the aging and at-risk work

They ask“Which tasks in my area are past their due date, and who is holding them?”

OutcomeBacklogs surface before they become escalations. Supervisors manage by exception instead of by status meeting.

Route a step to the right person

They ask“Who in this hierarchy is qualified for this review and has capacity this week?”

OutcomeWork is distributed on the basis of role and current load, rather than defaulting to whoever answers first.

Locate documents and case files

They ask“Find everything filed under this classification for this vendor since March, newest first.”

OutcomeStaff stop navigating folder trees by hand. Results respect the permissions the requester already holds.

Work with records and reference data

They ask“What retention policies are configured, and can you generate the report for these case records?”

OutcomeRecords staff answer policy questions and produce reporting without leaving the conversation — role restrictions still apply.

In every example the assistant acts as the requesting user, within the categories that connection is permitted to use — and every action is logged.

The Solution

A governed gateway between AI and your enterprise

The QAction® MCP Server is a secure connection point that lets MCP-compatible AI assistants work with the content and processes managed in QAction. It does not create a second copy of your information, a second permission model, or a second place for data to sit unsupervised. It applies the governance you already run.

MCP, Explained

A standard connector, not a custom integration

MCP stands for Model Context Protocol. It is an open standard that gives AI assistants a consistent, secure way to connect to business systems — much like USB created one standard way for devices to connect to a computer.

Before the standard existed, every AI-to-system connection was a custom project. Now an assistant that speaks MCP can connect to any system that speaks it too. Claude is one widely used example, and support across the industry continues to expand — so the connection you establish today is not tied to a single vendor’s tool.

The distinction that matters

MCP defines how the conversation happens. QAction defines what is allowed to happen.

GOVERNED INTELLIGENCE

QAction MCP Server Architecture

Governed AI access to enterprise information with identity, permissions, workflow rules, and auditability

Identity-aware

Policy-enforced

Fully audited

Identity Propagation

Every request carries the user's identity

Tool & Scope Enforcement

Only approved tools and scopes are exposed

Permissions & Workflow Rules

Permissions and workflow state are honored

Execution Guardrails

Validation, rate limits, and error handling

Governed Results

Only results the user is entitled to see

Auditability

Every action logged with identity + context

MCP SERVER

Customer
Identity Provider

SAML 2.0 / OIDC

User authentication

Entra ID / Okta / AD

SSO + MFA

Approved
AI Assistant

MCP client / AI application

User initiates the request

Receives governed results

No shared service account

QAction Content
& Data Systems

Documents

Tasks & Approvals

Workflows

Records & Data

Search & Retrieval

User Request

Authentication

Governed Response

Authorized Request

Content & Data Response

Audited Activity

QAction Audit Trail (Always On)

User Identity

Timestamp

Action

Tool

Result

Supports compliance
and discovery

MCP provides the connection standard. QAction provides identity, permissions, workflow rules, records controls, and auditability.

Four controls on every action

An assistant connected through the QAction MCP Server can do real work — find a document, claim a task, complete an approval, update a record. What makes that safe is not that it is limited to reading.

It acts as a person, not a robot account

The connection authenticates through your identity provider, and the server exchanges that sign-in for the user’s own QAction identity. Nothing runs under a shared integration credential.

You decide what it can see

Each connection is granted specific categories of work. Anything outside them isn’t merely blocked — those tools are never offered to the assistant at all, so it cannot attempt what it was never given.

No account, no access

A connection is admitted only for someone who already holds an active QAction account, with their existing permissions intact. If any part of that check fails, the session is refused rather than downgraded.

Everything is on the record — including refusals

Successful and denied actions alike are written to the QAction audit trail, tagged so AI-originated activity can be separated from ordinary user activity.

Business Value

Outcomes you already report on

Cycle time, risk exposure, audit readiness, and capacity. Not connectivity for its own sake.

Actions attributable to a person

Every call runs under the identity of the person who made the request — never a shared service account. When an auditor asks who approved something, the answer is a name, not an integration.

Scope you control

Each connection is limited to the categories of work you approve, managed from the connected apps page and adjustable at any time. Grant workflow access without granting the user directory.

Faster information access

Staff stop hunting across folders, classifications, and inboxes. They ask in plain language and get results drawn from content they are already authorized to see.

Work that moves

Assistants can claim tasks, complete routine approvals, place items on hold, and trigger workflow events — clearing the queues that quietly consume senior staff time.

Request a Demo

How It Works

Four steps. No new permission model.

No data duplication. No shared service account. No shadow access path.

The person signs in

The assistant connects through your identity provider and the person signs in as themselves. The server exchanges that sign-in for their QAction identity — no credentials are stored in the AI tool.

You set the scope

Each connection is granted only the categories of work you approve — tasks, documents, records, people. Anything outside them is never offered to the assistant, and grants can be changed at any time.

QAction applies your governance

A connection is admitted only for an active QAction user, and every request is validated against that person’s permissions, roles, and workflow rules. If any part of that check fails, the request is refused rather than allowed through with reduced identity.

The work gets done, and recorded

The assistant returns the result or completes the approved action. Both outcomes — and any refusal along the way — are written to the audit trail alongside every other action in the system.

GET STARTED

For your technical team

A short summary for architects and security reviewers. Full technical documentation is provided during evaluation.

Transport

An MCP Streamable-HTTP server exposing the QAction work management API as callable tools. Clients connect over OAuth 2.0 with S256 PKCE, protected-resource metadata (RFC 9728), and dynamic client registration — the standard path for MCP clients including Claude Code, the Claude desktop app, and hosted connectors.

Identity

Keycloak-secured. Incoming bearer tokens are validated against the realm and exchanged (RFC 8693) for per-user QAction identity, so every tool call executes as the calling user. There is no shared service account behind AI activity.

Admission

Fail-closed. A session is established only if the requester holds an active QAction account in that environment; any token exchange, registration, or network failure denies the session rather than degrading to a lesser identity.

Scope control

Tool access is consent-gated by scope. A connection is granted specific categories, and tools outside those categories are neither advertised to the assistant nor callable by it. Grants are managed in QAction and can be changed at any time.

Built by a governance company, not an AI startup

Plenty of tools can connect an AI assistant to a data source. Very few were built by a team that has spent more than two decades answering to auditors, records officers, and government oversight.

QFlow Systems has developed and implemented governed content, workflow, and records solutions for public sector and regulated organizations since 2000 — as both the product developer and the implementation partner. The QAction MCP Server did not begin as an AI product looking for a governance story. It began as a governance platform extending safely into AI.

Information governance expertise

Governance is the core discipline, not a compliance checkbox added late.

Enterprise content management

A mature content services platform managing documents, versions, metadata, and audit history as one system of truth.

Workflow automation

Processes with defined rules, roles, and approvals — so automation strengthens accountability rather than bypassing it.

Records management

Retention schedules, classification, legal hold, and defensible disposition aligned to NARA standards and organizational policy.

Proven in government and regulated environments

Long-standing service to federal agencies and regulated organizations, with a track record of delivery on time and within budget.

Get Started

Adopt AI on your terms

AI is entering your organization whether or not there is a plan for it. The question is not whether staff will use AI assistants — it is whether those assistants will operate inside your controls or around them.

The QAction MCP Server gives you a defensible path forward: a single, governed connection point where AI works with authorized enterprise information, under existing permissions, with a complete audit trail behind every action.

Request a demo

See what governed AI looks like in your environment. A QFlow specialist will follow up within one business day.

Let AI work with your enterprise information — under your rules