MCP API Translator

io.github.krishgokv0.4.1Updated Oct 11, 2026

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

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Overview

AI-generated overview

Turns OpenAPI or Postman API specs into runnable MCP server projects, or serves an API as live MCP tools.

What it does
Parses OpenAPI 3.0/3.1 or Postman v2.1 specs and scaffolds a complete TypeScript or Python MCP server project for that API. Its tools preview proposed tools before writing anything (analyze_spec), generate a project (generate_mcp_server), append another spec's tools to an existing project (extend_mcp_server), and report supported formats, auth schemes and limits (list_supported_features). It can also run a runtime proxy that exposes one or more APIs as MCP tools without generating code.
When to use it
Use it when you want an assistant to call a REST API through MCP and you want to own the resulting server code, curate which endpoints become tools, or combine several APIs into one server. It also fits quick, throwaway exposure of an API via the serve mode.
Requirements
Runs locally over stdio via npx with Node 20+, or as a Docker image. Specs are given inline or as a local path. Generated servers and the serve proxy need API base URLs and credentials supplied through environment variables (namespaced per API, listed in the generated .env.example); no credentials are declared for the translator itself.
Before you install
Generated servers and the serve proxy read API credentials from environment variables such as _API_KEY and _API_BASE_URL, so those secrets end up in the generated project's environment. Generated tools can call write, send or delete operations on the target API; curate endpoints rather than exposing a whole spec. Specs and API responses pass through the local process, and the README notes no interactive OAuth consent flows.

Installation

In SourceWeft

  1. Open MCP API Translator in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

mcp-api-translator

[npm] [CI] [License: AGPL-3.0] [Commercial license available] [MCP]

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.

[Curate a spec, aggregate a second one, run the generated server, and let an agent call it]

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:

bash
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):

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):

json
{  "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

ToolWhat it does
analyze_specParse a spec and preview the tools that would be generated — no files written.
generate_mcp_serverGenerate a complete MCP-server project into outputDir.
extend_mcp_serverAppend another spec's tools to an existing project (idempotent).
list_supported_featuresReport 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."

js
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:

js
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:

js
// any second API — the sources don't have to share a format or a vendorextend_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 (<NAMESPACE>_API_BASE_URL, <NAMESPACE>_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:

bash
cd petstore-mcp && npm install && npm run buildcp .env.example .env   # set API_BASE_URL + credentials (never embedded in code)npm start

Register it with your client using the generated client-config.md, and your agent can call the APIs directly.

Full walkthrough with sample outputs and troubleshooting: 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:

    bash
    mcp-api-translator serve --spec ./api.yamlmcp-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

DocWhat's in it
usage-workflow.mdEnd-to-end walkthrough, curation loop, auth setup, troubleshooting.
design.mdTech stack, generated project layout, limitations, security model.
deploy-serve.mdDocker/compose recipes for serve, logging and observability.
serve-api-proposal.mdDesign of the runtime proxy and the roadmap.
market-analysis.mdWhy both generate and serve models exist.
CONTRIBUTING.mdDev setup, PR conventions, DCO sign-off.

Known limits at a glance: OpenAPI 3.0/3.1 and Postman v2.1 (Swagger 2.0 best-effort), no GraphQL/gRPC; no interactive OAuth consent flows; no upstream streaming or auto-pagination; output quality tracks spec quality. Details and the security model: docs/design.md.

Development

bash
npm installnpm test          # unit + integration (parsers, curation, emit, append)npm run typechecknpm run buildnpm 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

mcp-api-translator is dual-licensed — © 2026 krishgok. Full details in LICENSING.md.

  • 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.

Source: README.md at commit f117273

Tools

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Version history

1
  1. v0.4.1LatestOct 11, 2026