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Let Your Customers Use Your Platform Through AI Agents

An MCP (Model Context Protocol) server lets your customers connect Claude, ChatGPT, and other AI agents to their account on your platform, built on the API you already have.

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How It Fits

A layer between your customers' AI agents and the platform you already run.

Your Customer
Asks in plain language
Their AI Agent
Claude, ChatGPT, and more
What I Build
MCP Server
Sign-inToolsDocs
Your Platform
Existing API and business logic

Built in your stack, on the API you already have.

See It in Action

A customer asks a question, and their agent uses your platform to answer it or take action.

AI Agent
Which orders are running late this week?
Usedsearch_ordersstatus: late · last 7 days
14 orders are late. 9 are from Acme Supply, averaging 6 days behind.
Pause Acme's listings until we sort it out.
Usedpause_listingssupplier: Acme Supply · 42 listings
Done. 42 Acme Supply listings are paused.

What an MCP Server Includes

Three parts, sized to your platform.

Secure Sign-In

Customers connect agents with the account they already have.

Claude wants to access your account
DenyAllow
Connected agents
ClaudeRevoke
ChatGPTRevoke

Tools

The actions an agent can take, built on your existing API.

GET /orderssearch_orders
POST /listings/pausepause_listings

Documentation

The context agents need to answer correctly about your platform.

margin

Sale price minus supplier cost and fees

ship_by

Set from the supplier's handling time

Optimized for AI

For large data sets, the heavy work runs on your server, so agents get small, useful answers. Examples:

Return Only What's Needed

"Is anything stuck? What's been waiting the longest?"

Instead of: Pages of full order records
Result: 25 rows, 4 fields
search:
  domain:  orders
  columns: order_number, supplier, ordered_at, error
  filters: status = awaiting_shipment
           ordered_at before 5 days ago
  limit:   25

Aggregate on the Server

"Which suppliers ship late most often?"

Instead of: Exporting shipments and running a script
Result: One summary row per supplier
analyze:
  domain:     shipments
  metrics:    count(*), rate(is_late), avg(days_to_ship)
  dimensions: supplier
  filters:    status = shipped

Act in Bulk

"Pause listings from that supplier while we sort out the problem."

Instead of: 42 separate API calls
Result: One request, checked against the expected count
act:
  domain:         listings
  action:         pause
  filters:        supplier = "Acme Supply"
                  status = active
  expected_count: 42

Scope That Grows With Your Platform

Scope depends on your data and what your customers need from it.

Start
Connect
Sign-inA few tools

Customers handle common tasks through their agent

Add
Context
DocumentationMore tools

Agents answer detailed questions correctly

Scale
Optimize
AggregationBulk actions

Analysis and changes across large data sets

How an MCP Server Gets Built

Scope varies from platform to platform. The work moves through these phases.

  1. 1

    Find the Value

    Start with what your customers would ask an agent. The most valuable questions often mean analyzing and correlating data across your platform.

  2. 2

    Plan the Approach

    For each capability: does it map to an existing endpoint, or need new functionality? Decide how sign-in works and where the server runs.

  3. 3

    Build It

    Built with patterns your developers already know. Scope decides whether it's a separate package or part of an existing API. Documentation and agent instructions are part of the build.

  4. 4

    Test With Real Agents

    Real customer questions run in Claude and ChatGPT. When an agent gets something wrong, the tools or documentation are adjusted until it gets it right.

Also part of the build
  • Permissions per user
  • Rate limits
  • Audit logging
  • Errors written for agents
  • Versioning as your API changes

Recent Client Work

Flxpoint

Flxpoint

Planned and led development of the MCP server that lets Flxpoint customers connect AI agents to their operations data and actions

"What you've done here is well above and beyond what we were expecting. It's set us up for future growth."

Brad · Chief Architect at Flxpoint

Ready to Open Your Platform to AI Agents?

Let's talk about what your customers want agents to do and what an MCP server for your platform would need.