MCP & Agent Readiness
Make your systems callable by Claude, ChatGPT, and the agent ecosystem — MCP servers over your APIs with real authentication, published discovery surfaces, and governance over which agents may do what.
What it is
Your customers and employees now arrive with an AI assistant attached — Claude, ChatGPT, a coding agent, an AI browser. MCP & Agent Readiness makes your product and your internal systems first-class citizens of that world: an MCP server over your API so assistants can call it safely, discovery surfaces so agents find you, and governance so 'an agent can reach it' never means 'any agent can do anything'.
Why it matters
MCP has become the de facto standard for connecting AI to tools — adopted across Claude, ChatGPT, IDEs, and agent frameworks. Being reachable through it is quickly becoming what having an API was in 2015: table stakes for anyone whose customers integrate. Companies that expose a governed MCP surface early get discovered by assistants; the rest get scraped, misquoted, or skipped.
What we build
One readiness track covering both directions — your systems exposed to agents, and outside agents governed inside your walls.
- An MCP server over your existing API — OAuth 2.1, scopes, rate limits
- Claude and ChatGPT readiness: connectors, actions, and the auth flows each expects
- Published discovery: Agent Skills, llms.txt, WebMCP tools in your pages
- A tool registry governing which agents see which tools, with audit trails
- BYO-agent policy for staff: a vetted MCP catalog instead of a ban nobody follows
- Generated from your OpenAPI spec where one exists — no parallel integration to maintain
What it works with
Builds on the AI Platform's gateway and the MCP Tool Registry for governance. The packaged expression for public sites is Concierge Beacon; Library MCP covers governed access to a private document corpus. Our own production platform serves its full API as an MCP server with OAuth 2.1 — the pattern arrives already debugged.
When you need it
Customers ask whether your product 'works with Claude' or 'has a ChatGPT integration' and the honest answer is not yet. Partners want API access their agents can use. Your staff already paste data into assistants, and you would rather govern the connection than pretend it isn't happening.
Related learning
Anthropic's open standard for exposing tools, resources, and prompts to AI models — released in late 2024, broadly adopted across the agent ecosystem, the connective tissue of modern AI tool integration.
A governed catalog of every tool an AI agent can call — your APIs, your databases, your internal systems — with typed schemas, permission scopes, audit trails, and the standard protocol (MCP) that turns 'we exposed it to the LLM' into 'we know exactly who called what when'.
An open, folder-based format for packaging procedural knowledge an AI agent loads on demand — instructions, scripts, and resources in a SKILL.md the agent reads only when a task calls for it.
A proposed web standard that lets a page expose MCP-style tools to agents running in the browser — navigator.modelContext — so a site becomes callable by agents, not just readable.
Your website, readable and callable by AI agents. A public MCP server, published Agent Skills, llms.txt, and in-page WebMCP tools — so when a customer's assistant asks about your product, the answer comes from you.
One operating layer for the AI models, tools, and data your teams use. Cost, quality, and governance you can see. Provider choices — hosted, local, or self-hosted — you can change without rewriting the system.