MCP API Translator
Turn OpenAPI / Postman specs into runnable MCP servers, or serve any API as live MCP tools.
Installation
Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).
mcp-api-translatorclaude mcp add mcp-api-translator -- npx -y mcp-api-translator@0.4.1
{
"mcpServers": {
"mcp-api-translator": {
"command": "npx",
"args": [
"-y",
"mcp-api-translator@0.4.1"
]
}
}
}
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
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
(<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:
cd petstore-mcp && npm install && npm run build
cp .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:
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
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.
Questions fréquentes
Qu'est-ce que MCP API Translator ?
Turn OpenAPI / Postman specs into runnable MCP servers, or serve any API as live MCP tools.
Comment installer MCP API Translator ?
Il s'exécute sur votre machine. Dans Claude Code : claude mcp add mcp-api-translator -- npx -y mcp-api-translator@0.4.1. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.
Faut-il une clé API pour MCP API Translator ?
Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.
MCP API Translator est-il open source ?
Oui. Son code est sur GitHub sous licence AGPL-3.0.
Qui maintient MCP API Translator ?
Il est publié par krishgok. AI.tn le référence sans le maintenir ni le recommander.
Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.