mcp-builder

mcp-builder

Team Pick
AI & Agents
Anthropic
The path from an API with no connector to a working MCP server, judged on whether an agent can complete tasks with it and not on endpoint coverage.
REPO
anthropics/skills
INSTALL
Claude Code plugin
NEEDS
API docs
Last updated
August 4, 2026

Preview

mcp-builder

What it is.

It takes you from an API with no connector to a working MCP server across four phases, recommending TypeScript with streamable HTTP and stateless JSON, and pointing you at the protocol spec to read before you write anything.

For a marketing team this is how the tool holding your pipeline data stops needing a weekly export. The quality bar is whether an agent can finish a task with it, so tool naming, concise descriptions, pagination and filtering all count, and error messages have to suggest a next step.

What you get.

  • Four phases from research through implementation, with a stack recommendation
  • Tool naming and description guidance, using consistent prefixes
  • Context management rules, so tools return focused results instead of everything
  • Error message guidance aimed at what an agent should try next
  • Language guides for TypeScript and Python, plus a best practices reference
HOW TO USE IT

How to set it up.

1

Install the example-skills plugin from the anthropics/skills marketplace.

2

Decide between workflow tools and full endpoint coverage. The skill's advice when you are unsure is to prioritize coverage, because it gives the agent room to compose.

3

Read the protocol specification through the sitemap, fetching pages with a markdown suffix so they arrive readable.

4

Pick TypeScript unless you have a reason. It is the recommended language, with streamable HTTP and stateless JSON for remote servers.

5

Name tools with a consistent prefix and an action, such as a service name followed by the verb, so an agent can find the right one.

6

Add pagination and filtering from the start. A tool returning everything spends the agent's context on data it did not need.

Pricing Plans

Free. Apache 2.0 license.

Included in Anthropic's example-skills plugin. Checked against the repo in July 2026.

Use cases

Wrapping the billing API

Your billing tool has an API and no connector. Feed the skill the API documentation and work through its four phases, and a TypeScript server comes out that Claude can call directly.

Retiring the weekly export

Pipeline questions currently wait for a Monday export. Wrap the tool holding that data in a server, and from then on the numbers get pulled live in conversation.

Design pass on a rough server

You built a server and agents fumble it. Run the naming, description, pagination and error-message guidance over it, so each tool returns focused results and every failure names a next step.

Coverage or workflows, decided

You're unsure whether to build a few workflow tools or wrap the whole API. The skill's stated advice when in doubt is coverage, because it leaves the agent room to compose.

Best for

A CRM or billing tool with no connector

An API and no MCP server is the exact gap this closes, and most GTM data still sits behind one.

Replacing a weekly export

Once the server exists, the question gets asked in a sentence and the export step disappears.

Building an internal tool for the whole team

One server, and every skill on this page can query it, which is a better payoff than a one-off script.

Read the source

Published by Anthropic. Opens in a new tab.
Open the Tool

Questions about mcp-builder

Which language should I use?
Workflow tools or full API coverage?
Do I need to be a developer?
How do I know the server is any good?

Questions about AI & Agents

What makes an API worth wrapping?
What should a connector expose?
Strengths
  • Judges the server on task completion instead of on how many endpoints it exposes.
  • Names the stack and the transport, so the first decision is already made.
  • Treats error messages as agent instructions, which is a design point most API wrappers miss.
  • Points at primary protocol documentation instead of summarizing it and going stale.
Limitations
  • This is engineering work. It shortens the path and it will not remove the need for someone who writes code.
  • You still handle authentication and secrets yourself, which is where a marketing team usually needs help.
  • A demonstration skill, with Anthropic's caveat attached.
Skip this if
  • Skip it if the API you need already has a connector.

The team behind these plays.

We build inbound GTM engines for B2B software teams, and these are the plays we build from. Tell us the pipeline target and we'll show the plan under it.