Product context for AI assistants

Plan a safe path into governed AI.

Rooksy helps organizations turn APIs and databases into governed MCP tools, manage company AI policies, control sensitive agent actions, collect audit evidence, and connect execution traces to their observability stack.

Open raw brief

Product workflow

Seven steps, one governed path.

  1. 01

    Connect

    Import OpenAPI 3.x from a URL or file, describe REST endpoints manually, or explore a database schema using temporary read-only access.

  2. 02

    Discover

    Inspect operations and propose useful MCP tools from endpoints, parameters, request bodies, and response schemas.

  3. 03

    Design

    Select tools, rename them, improve descriptions, edit input and output schemas, assign owners, and classify risk.

  4. 04

    Test

    Run tool calls in a playground, inspect structured output, and exercise approval gates for write and destructive actions.

  5. 05

    Govern

    Apply approval rules, separation of duties, policy mappings, retention requirements, and evidence controls.

  6. 06

    Publish

    Release an approved tool bundle as a remote MCP endpoint with a ready-to-use client configuration.

  7. 07

    Observe

    Review invocations and approval decisions, then export or route telemetry to existing observability and security systems.

Current prototype

Available now for exploring and validating the complete product experience.

  • Polished end-to-end product workflow and interactive workspace
  • OpenAPI, REST, and database-source configuration experiences
  • Tool selection, naming, descriptions, schemas, and risk classification
  • Tool Studio, MCP Playground, approval inbox, governance center, publishing, integrations, and invocation logs
  • Local browser persistence and a demo runtime suitable for product exploration
  • Policy Vault with company-profile suggestions, document scanning, editable versions, signatures, and policy MCP exposure
  • People and access preview with Policy Owner roles, company SSO boundary, and simple governance pricing
  • AI operations preview with OpenRouter model routing, privacy controls, budgets, and cost reporting

Production gaps

Requirements an onboarding plan must treat as dependencies, not delivered capabilities.

  • Real outbound API and database execution across all connectors
  • Encrypted managed secrets, enterprise OAuth, SSO, SCIM, and tenant isolation
  • Durable multi-person approval workflows, notifications, escalations, and SLAs
  • Production MCP runtime isolation, version promotion, rollback, and regional controls
  • Verified regulatory evidence exports or a guarantee of legal compliance
  • Production billing, usage enforcement, and contractual service levels
  • Production SSO, SCIM, encrypted policy storage, document extraction, and multi-party signature delivery

What it enables

One control plane from source to evidence.

  • 1Create a governed MCP capability from an existing API or data source
  • 2Give every tool a clear owner, schema, risk level, and approval policy
  • 3Require human approval before write or destructive operations execute
  • 4Publish an MCP endpoint with a client configuration teams can use
  • 5Keep a searchable record of calls, decisions, actors, and outcomes
  • 6Map operational evidence to EU, UK, US, and industry governance frameworks
  • 7Send correlated telemetry to tools such as Langfuse, OpenTelemetry, Datadog, and SIEM platforms
  • 8Create a company Policy Vault with AI-assisted review, signatures, mailbox guardrails, and a policy MCP
  • 9Give Owners, Admins, Legal, Compliance, and Security teams a shared control surface

Discovery checklist

What an onboarding planner needs to learn.

  • 1Organization, business unit, executive sponsor, and technical owner
  • 2The first agent workflow and the business outcome it should improve
  • 3AI clients or agent platforms that will consume MCP tools
  • 4Source APIs, databases, environments, authentication methods, and system owners
  • 5Candidate read, write, financial, privileged, or destructive actions
  • 6Data classifications, residency constraints, and retention requirements
  • 7Applicable governance frameworks and internal policies
  • 8Approvers, delegation rules, separation-of-duties needs, and response SLAs
  • 9Existing observability, security, ticketing, and evidence systems
  • 10Pilot population, success metrics, rollout constraints, and target dates

Expected output

What a useful onboarding plan should contain.

  • 1A phased 30/60/90-day onboarding plan with owners and exit criteria
  • 2A first-use-case recommendation and explicitly deferred use cases
  • 3A source-to-tool inventory with proposed risk levels
  • 4An approval matrix covering read, write, privileged, and destructive actions
  • 5An identity, secrets, environment, and access-control design
  • 6A test and validation plan for schemas, policy behavior, and failure modes
  • 7An observability, audit evidence, retention, and incident-response design
  • 8A pilot-to-production rollout plan with measurable success criteria
  • 9A gap and dependency list that separates current product capabilities from required future work

Ready for a planning session

Share one link. Start with the right questions.

The raw brief is intentionally concise, machine-readable, and honest about the current boundary between prototype and production.