MCP
What is an MCP server?
An MCP server is a small interface that lets an AI agent discover tools and call them in a predictable way. Instead of pasting API docs into a prompt and hoping the model gets it right, the agent asks the MCP server what tools exist, what inputs they need, and what happened when a call ran.
The simple version
MCP means Model Context Protocol. It gives agents a standard way to connect to tools, data, and actions. A good MCP server does not just expose raw API routes. It gives the agent names, schemas, auth boundaries, and runtime feedback.
That matters because agents are not humans reading docs. They need tight instructions, stable inputs, and clear errors. If a tool is ambiguous, the agent wastes tokens, retries the wrong thing, or asks the user for information it could have discovered.
What Astrail adds
Astrail generates hosted MCP servers from OpenAPI specs, public websites, and workflow descriptions. The output is an endpoint your agent can call, plus metadata for tools, credentials, runtime mode, logs, and SDK exports.
The point is to make MCP feel less like infrastructure work and more like installing a package. Pick a server, bring credentials when needed, and connect it to Claude, Cursor, ChatGPT, or your own agent runtime.
When you need one
Use an MCP server when an agent needs to do real work: search tickets, create invoices, update CRM records, inspect files, run browser workflows, or call internal APIs. The server becomes the narrow bridge between the agent and the system.
If the work is high risk, you want an MCP layer even more. It lets you define what tools exist, which calls require auth, what is public, and what should stay private.
FAQ
Is an MCP server the same as an API?
No. An API is usually built for developers. An MCP server wraps tools for agents with schemas, names, and runtime behavior that models can use.
Can Astrail host the MCP server?
Yes. Astrail is built around hosted MCP endpoints, generated tool metadata, logs, auth boundaries, and SDK exports.