MCP And Agent Connectors
Let AI agents use your marketplace without bypassing trust
We build secure connector layers that let approved AI systems search listings, check availability, qualify leads, create support tickets, and help operations while respecting permissions, logs, and human approval paths.
Agent Permission Console
Actions are scoped before the agent gets a tool
Search listings
Find listings, providers, products, rentals, or categories.
Check availability
Query available time slots, inventory, or capacity.
Create support ticket
Open a tracked issue with user context and escalation rules.
Send provider message
Draft allowed; sending should require human review.
Refund payment
Payment actions need a separate approval and security path.
We design the connector so an agent can be useful without becoming over-permissioned. Risky actions need explicit approval paths.
FOCUSED WORKFLOWS
The strongest agent connectors start with one specific job
The first connector should solve a high-friction marketplace workflow, not expose every system action at once.
Buyer Concierge
Help buyers describe intent, compare options, check availability, and route into quote, booking, or checkout flows.
Provider Onboarding
Turn supplier URLs, PDFs, spreadsheets, and rough descriptions into structured listings that humans approve.
Support And Dispute Intake
Summarize policy context, order history, booking status, and escalation paths before support teams act.
Internal Ops Reporting
Surface stale listings, supply gaps, booking anomalies, provider quality risks, and weekly operating summaries.
TECHNICAL SCOPE
What we build
Our connectors expose useful marketplace actions through controlled APIs, not fragile prompt-only automation.
Connector Architecture
Identity And Permissions
Safety And Approval Gates
Observability
PROCESS
From action map to verified connector
A connector is only useful when it is narrow enough to trust. We define permissions before implementation and test failure modes before launch.
Action Map
Define which marketplace workflows an agent can read, draft, suggest, or execute.
Permission Model
Design scoped access, tenant isolation, account linking, and approval rules before exposing tools.
Connector Build
Implement tools, resources, validation, logs, rate limits, and fallback behavior.
Eval And Launch
Test realistic scenarios, failure modes, prompt injection attempts, and handoff rules before production use.
Action Map
Define which marketplace workflows an agent can read, draft, suggest, or execute.
Permission Model
Design scoped access, tenant isolation, account linking, and approval rules before exposing tools.
Connector Build
Implement tools, resources, validation, logs, rate limits, and fallback behavior.
Eval And Launch
Test realistic scenarios, failure modes, prompt injection attempts, and handoff rules before production use.
CAVEATS
Useful agents need boring controls
We build connector systems that make agents useful while keeping external sends, payments, deletion, publishing, and other high-risk actions behind explicit approval paths.
External agent surfaces and provider capabilities may change.
The platform needs structured data and APIs before action tools are reliable.
Payment, refund, deletion, and outbound communication actions need separate security review.
Directorism builds the connector and guardrails; we do not guarantee acceptance by any external AI platform.
ENGAGEMENT PATHS
Start with the smallest agent that earns trust
Most marketplaces should not jump straight to autonomous actions. We help founders choose the first useful connector based on data readiness, workflow risk, and team capacity.
QUESTIONS
Marketplace agent connector FAQ
The strongest first connector is usually narrow, observable, and tied to a workflow your team already understands.