MCP API Translator

Name: MCP API Translator
Author: krishgok

by krishgokversion 0.4.1i★ –iRuns on your computer

Registry nameio.github.krishgok/mcp-api-translator

Install

Overview

Description from the maker (original English)

Turn OpenAPI / Postman specs into runnable MCP servers, or serve any API as live MCP tools.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "api-translator": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-api-translator"
      ]
    }
  }
}

Run this in your terminal

claude mcp add api-translator -- npx -y mcp-api-translator

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "api-translator": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-api-translator"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "api-translator": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "mcp-api-translator"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account krishgok, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32564 servers in this category
Published to the registry more recently than 59% of the other 32564 servers in this category
Basic checks equal to or better than 100% of the other 32564 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MCP API Translator safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.4.1) reached the registry 27 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Tools MCP

Alternatives

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

mcp-api-translator

An MCP server that generates MCP servers. Give it an API definition — OpenAPI 3.0/3.1 or a Postman collection — and it scaffolds a complete, runnable, _ownable_ TypeScript or Python MCP server for that API.

_Above: curating Firecrawl's 20 operations down to 6, appending the Gmail API to the same server, then an agent calling the self-hosted result. Counts, tool names and paths come from real runs against the published Firecrawl and Gmail descriptions; the API responses are illustrative — the recording runs against a local stub, not live Firecrawl or Gmail accounts._

Why this and not a 1:1 generator

Turning an OpenAPI spec into MCP "tool stubs" is not novel — FastMCP's from_openapi, Speakeasy/Gram, and several openapi-mcp-generator projects already do the mechanical part. A naive endpoint→tool generator has no real advantage. This project focuses on the parts those tools skip:

1. Curation, not just generation. A 200-endpoint API naively becomes 200 tools, which wrecks a model's tool-selection accuracy and blows out context. analyze_spec previews the tool list before anything is written, every command takes includeTags / methods / pathGlob / excludeOperations, and you get a warning when a server grows past 40 tools.

2. Aggregation via append. extend_mcp_server adds another API's tools to an existing project, so you can build one MCP server spanning Firecrawl + Gmail + your internal API. Credentials stay separate: each API also reads namespaced env vars derived from its title.

3. An artifact you own. Output is a normal project, not a hosted black box — readable per-tool files, env-based auth, a Dockerfile, and a server.json plus client snippets for publishing to the official MCP Registry.

If you only need throwaway, in-memory exposure of one API and don't care about owning the code, FastMCP's runtime mode may suit you better — that's a deliberate non-goal here.

Install

No install step. npx fetches and runs the latest published version — cross-platform, Node 20+.

Claude Code

Claude Code does not read claude_desktop_config.json — it keeps its own MCP config:

claude mcp add api-translator -- npx -y mcp-api-translator

That registers it at local scope. Use -s user for all your projects, or commit a project-scoped .mcp.json to share it. Verify with claude mcp list.

Claude Desktop

Add to claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%\Claude\claude_desktop_config.json):

"mcpServers": { "api-translator": { "command": "npx", "args": ["-y", "mcp-api-translator"] } } }

Cursor, Cline, Continue.dev, Docker

Cursor — ~/.cursor/mcp.json (or project-scoped .cursor/mcp.json), same mcpServers shape as Claude Desktop above.

Cline (VS Code) — sidebar → MCP Servers → Configure, same shape plus "disabled": false.

Continue.dev — ~/.continue/config.json, under experimental.modelContextProtocolServers, as a { transport: { type: "stdio", command, args } } entry.

Docker (no Node required):

"mcpServers": { "api-translator": { "command": "docker", "args": ["run", "--rm", "-i", "ghcr.io/krishgok/mcp-api-translator:latest"] } } }

To read specs from disk or write projects to a host path, mount the directory with -v ${PWD}:/workspace and pass /workspace/... as specPath / outputDir.

MCP config is read at startup, so restart your client — quit and reopen Claude Desktop, Cursor, …, or start a new session in Claude Code.

The four tools

Tool	What it does
`analyze_spec`	Parse a spec and preview the tools that would be generated — no files written.
`generate_mcp_server`	Generate a complete MCP-server project into `outputDir`.
`extend_mcp_server`	Append another spec's tools to an existing project (idempotent).
`list_supported_features`	Report supported formats, auth schemes, transports, and limits.

All spec inputs accept inline text (spec) or a local path (specPath), JSON or YAML.

Usage

You don't call the tools by hand — you ask your agent, and it drives them.

1. Preview, then curate. See what a spec becomes before writing anything:

_"Analyze ./petstore.yaml and show me the proposed tools."_

_"Only the GET endpoints under /pets."_

analyze_spec({ specPath: "./petstore.yaml" });

// → proposed tool list, auth scheme, and the env vars the server will need

analyze_spec({ specPath: "./petstore.yaml", methods: ["GET"], pathGlob: "/pets/**" }); // also: includeTags: ["pets"], excludeOperations: ["deletePet"]

2. Generate, with the same filters plus an output directory:

generate_mcp_server({ specPath: "./petstore.yaml", outputDir: "./petstore-mcp" });

// options: language: "python", transport: "http", auth: {...}, force: true

3. Aggregate — add more APIs to the same server:

// any second API — the sources don't have to share a format or a vendor

extend_mcp_server({ projectDir: "./petstore-mcp", specPath: "./billing.postman.json", includeTags: ["invoices"], }); // idempotent; hand-edited tool files are preserved

Aggregated APIs don't share credentials: each also reads namespaced env vars ( _API_BASE_URL, _API_KEY, … — namespace derived from the API title) before falling back to the bare ones. The extend summary and .env.example list the exact names.

4. Run it. The output is a normal project you own:

cd petstore-mcp && npm install && npm run build

cp .env.example .env # set API_BASE_URL + credentials (never embedded in code) npm start

Full walkthrough with sample outputs and troubleshooting: [docs/usage-workflow.md](docs/usage-workflow.md).

Generate, or serve

Generate ownable code when you want a project you can hand-edit, self-host, and own — in TypeScript (default) or Python (language: "python").
Serve a live runtime proxy when you just want an API exposed to an agent now, with no generated files to build or maintain:

  mcp-api-translator serve --spec ./api.yaml

mcp-api-translator serve --spec ./a.yaml --spec ./b.yaml --methods GET,POST # aggregate

serve runs the same request plan and env-based auth the generator emits, so behavior matches generated output exactly — it just skips the codegen step. It speaks stdio by default, or stateless Streamable HTTP with --transport http --port 3000. Logs are structured JSON lines on stderr in containers, readable text on a TTY (LOG_LEVEL, LOG_FORMAT).

Documentation

Doc	What's in it
usage-workflow.md	End-to-end walkthrough, curation loop, auth setup, troubleshooting.
design.md	Tech stack, generated project layout, limitations, security model.
deploy-serve.md	Docker/compose recipes for `serve`, logging and observability.
serve-api-proposal.md	Design of the runtime proxy and the roadmap.
market-analysis.md	Why both generate and serve models exist.
CONTRIBUTING.md	Dev setup, PR conventions, DCO sign-off.

Known limits at a glance:

Inputs: OpenAPI 3.0/3.1 and Postman v2.1 (Swagger 2.0 best-effort). GraphQL and gRPC aren't supported.
Auth: no interactive OAuth consent flow yet for the OpenAPI/Postman APIs it does support; planned as R6.
Responses: no upstream streaming or auto-pagination.
Output quality tracks spec quality.

Details and the security model: docs/design.md.

Development

npm install

npm test # unit + integration (parsers, curation, emit, append) npm run typecheck npm run build npm run e2e # generate a sample project from the fixtures into build/e2e-out

Contributions welcome — see CONTRIBUTING.md. All commits must be signed off under the Developer Certificate of Origin (git commit -s).

License

Open source: GNU AGPL-3.0-or-later. Running a modified version as a network service requires offering that version's complete source to its users.
Commercial: a separate license is available for embedding in proprietary products without AGPL obligations.
Your generated output is yours. Projects produced by this tool are covered by a generated-output exception and are not subject to the AGPL.

Redistributions must retain LICENSE and NOTICE. The licenses do not grant the right to use the "mcp-api-translator" name to endorse or promote forked or derivative works without prior written permission.

MCP API Translator

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Tools MCP

README from the maker

mcp-api-translator

Why this and not a 1:1 generator

Install

Claude Code

Claude Desktop

The four tools

Usage

Generate, or serve

Documentation

Development

License