모든 OpenAPI REST API를 Claude Code 및 Cursor와 같은 AI 클라이언트에서 사용할 수 있는 프로덕션급 MCP server로 변환합니다.
다른 이름 furkan708/mcpify, mcpify-openapi
- 스타
- 2
- Tools
- —
- 다운로드, 30일
- 414
- 최신 버전
- 1.19.0
- 마지막 커밋
- 2026년 9월 4일
- 라이선스
- MIT
mcpify MCP란?
mcpify은(는) MCP server입니다. 모든 OpenAPI REST API를 Claude Code 및 Cursor와 같은 AI 클라이언트에서 사용할 수 있는 프로덕션급 MCP server로 변환합니다.
프로젝트 README에서 생성된 요약
mcpify MCP server 정보
개발자는 모든 OpenAPI 3.x REST API를 기능적인 MCP server로 변환하여 Claude Code 및 Cursor와 같은 AI 클라이언트에서 직접 상호작용할 수 있습니다. CLI를 통해 명세 파일이나 URL을 지정하면, 모든 API 작업이 에이전트가 탐색하고 실행할 수 있는 일급 도구(first-class tool)로 자동 변환됩니다. 이 프로세스는 표준 웹 서비스와 Model Context Protocol 사이의 간극을 메우기 위해 단 한 번의 명령만으로 빠르게 처리되도록 설계되었습니다.
보안과 효율성은 구현의 핵심입니다. 사용자는 환경 변수를 통해 자격 증명을 관리하여 비밀 정보가 모델에 노출되지 않도록 할 수 있으며, redact 플래그를 사용하여 읽기 전용 액세스나 비밀 정보 마스킹과 같은 엄격한 정책을 적용할 수 있습니다. 이 server는 팀 단위 배포를 위해 로컬 stdio 전송과 원격 HTTP/SSE 연결을 모두 지원합니다. 또한 특정 필드만 선택하는 응답 프로젝션(response projection)이나 AI에 전송되는 컨텍스트 예산을 줄이기 위한 지연 로딩(lazy loading)과 같이 토큰 사용량을 관리하는 특화된 기능도 포함되어 있습니다.
활용 사례
- 1에이전트를 위한 안전한 API 액세스AI 에이전트의 권한을 읽기 전용 작업으로 제한하여 세션 중 의도치 않은 데이터 변형을 방지합니다.
- 2여러 API의 동시 관리통합된 상태 모니터링을 제공하는 단일 MCP server 인스턴스에 여러 개의 서로 다른 OpenAPI 문서를 결합합니다.
프로젝트의 README를 바탕으로 작성되었습니다. 모든 활용 사례는 해당 내용의 인용문과 대조하여 확인합니다.
mcpify MCP 설치 방법
형식 확인: 2026년 11월 10일Cursor에 추가Goose에 추가Claude Code에 mcpify MCP 설치
$ claude mcp add mcpify -- uvx mcpify-openapiCursor에 mcpify MCP 설치
~/.cursor/mcp.json
{
"mcpServers": {
"mcpify": {
"command": "uvx",
"args": [
"mcpify-openapi"
]
}
}
}VS Code에 mcpify MCP 설치
.vscode/mcp.json
{
"servers": {
"mcpify": {
"type": "stdio",
"command": "uvx",
"args": [
"mcpify-openapi"
]
}
}
}VS Code CLI에 mcpify MCP 설치
$ code --add-mcp '{"name":"mcpify","type":"stdio","command":"uvx","args":["mcpify-openapi"]}'Claude Desktop에 mcpify MCP 설치
claude_desktop_config.json
{
"mcpServers": {
"mcpify": {
"command": "uvx",
"args": [
"mcpify-openapi"
]
}
}
}Codex에 mcpify MCP 설치
$ codex mcp add mcpify -- uvx mcpify-openapiCodex config.toml에 mcpify MCP 설치
~/.codex/config.toml
[mcp_servers.mcpify] command = "uvx" args = ["mcpify-openapi"]
Gemini CLI에 mcpify MCP 설치
$ gemini mcp add -s user mcpify uvx -- mcpify-openapiGemini settings.json에 mcpify MCP 설치
~/.gemini/settings.json
{
"mcpServers": {
"mcpify": {
"command": "uvx",
"args": [
"mcpify-openapi"
]
}
}
}구성
OAUTH2_CLIENT_IDOAUTH2_CLIENT_SECRETPETSTORE_KEY
| 이름 | 설명 | 유형 |
|---|---|---|
| OAUTH2_CLIENT_ID | — | |
| OAUTH2_CLIENT_SECRET | — | |
| PETSTORE_KEY | — |
자동 검사
2026년 11월 14일에 실행됨전체 보고서 →자동 검사를 통과했습니다. 이는 보안 감사가 아닙니다. 코드를 직접 읽고 서버에 필요한 최소한의 권한만 부여하십시오. 검사 방식
- 소스 저장소 연결 및 접근 가능furkan708/mcpify is public and reachablegithub.com/furkan708/mcpify ↗통과
- 패키지가 이 저장소를 소스로 명시검사되지 않음
- 빌드 출처(Sigstore 증명)Sigstore attestation for mcpify-openapipypi.org/project/mcpify-openapi/ ↗통과
- 오픈 소스 라이선스 (OSI)MITspdx.org/licenses/MIT.html ↗통과
- 최근 1년 내 커밋 또는 릴리스Last commit or release 2026-09-04github.com/furkan708/mcpify ↗통과
- OpenSSF Scorecard검사되지 않음
- 패키지 이름이 인기 패키지와 유사하지 않음No popular package one edit away from mcpify-openapi통과
- 패키지 및 해당 종속성에 중요한 보안 권고 없음1 resolved dependencies checked; no critical advisoryosv.dev ↗통과
- 모델에 대한 숨겨진 지침 없음0 tool descriptions and the README read; no override phrases, credential paths or hidden characters통과
- 파괴적인 도구에 라벨 표시됨검사되지 않음
- 원격 엔드포인트가 MCP 핸드셰이크에 응답검사되지 않음
README
GitHub에서 보기mcpify
English | Türkçe
Turn any OpenAPI REST API into an MCP server — so Claude Code, Cursor, and every other MCP client can call your API directly. One command, zero runtime dependencies:
mcpify serve https://your-company.com/openapi.json
# try it right now, nothing installed (uvx pulls from PyPI on demand)
uvx --from mcpify-openapi mcpify list examples/petstore.json --cost
Focused, production-ready, CLI-first: one job (OpenAPI → MCP). Everything else — governance, credentials, token economics, operations — is opt-in and stays out of the way until you need it:
- Safe for agents by default — lazy context budget (
--lazy), secret masking (--redact), blast-radius limits (--read-only, per-token RBAC) - Ready for real deployments — stdio + HTTP/SSE, OAuth2 and split read/write credentials, health probes, audit trail, metrics, multi-API serving, hot reload
- Proven, not promised — 520 tests across twenty-eight suites, a hostile-spec corpus, live-CI checks, zero runtime dependencies
Why you'll like it
From spec to server
- 60 seconds to working — point it at any OpenAPI 3.x spec (file or URL)
- Every operation becomes a first-class MCP tool — input schemas are generated from
parameters+requestBody, internal$refs are resolved - Spec versions diffed from the tool view —
mcpify diff old.yaml new.yamlreports added/removed/changed operations with per-change breaking verdicts and a migration guide;--fail-on-breakingis a CI gate mcpify doctor— tells you if your spec is agent-friendly before you ship: missing operationIds, missing summaries, instruction-like tool text, overlong descriptions;--probedials the API once — with your real credential (--auth-env) when you want auth proven end-to-end, and--fail-on-http-errorfor a strict CI gatemcpify try/mcpify mock/mcpify output-server— call the tools without an agent client, serve a schema-shaped fake API for CI, or bake a serve command into a shareable script
Credentials & policy
- Credentials never touch the spec or the model — pulled from your environment at call time; the spec's own security declarations pick the flags (bearer, basic, header, query)
- OAuth2 client-credentials built in — tokens are fetched, cached, refreshed and re-fetched on a mid-flight 401 (RFC 6749, stdlib only);
--write-oauth2-*gives non-GET calls a second client identity so reads and writes authenticate as different clients - Least-privilege by default —
--write-auth-envsplits the static credential (reads on your read key, writes on a dedicated key),--read-onlyfilters the surface,--deny/--allowhides mutating GETs, per-token RBAC gives each bearer token its own allow/deny scopes --redact password,token— values whose key names a secret are masked with***at every level of every response (error bodies included, case-insensitive); the model never sees them- Audit trail without content exposure — one JSON line per call: tool, API, status, latency, an argument fingerprint (never raw arguments);
--pluginloads your Python module for auth/request/result hooks
Token economics
- See the bill before serving —
mcpify list --costprices the surface (~4 chars/token): what every agent pays in EVERYtools/list; multi-API configs get per-API and total prices in one run --fields id,event— response projection that selects at every level: selected keys keep their value, non-selected containers stay transparent, emptied containers drop. Live weather.gov: 350 alerts in full inside the budget that previously truncated at ~189- Valid truncation — oversized responses are cut along JSON structure with an explicit
"truncated": truemarker, never mid-document --lazysearch-then-call — cut api.weather.gov's listing by 95.5%; search results now show what pulling each full schema would cost, so the agent pulls only what it needs[tool-text]overrides — doctor flags model-facing instruction-like descriptions; you replace them per tool in config
Operations
- Two transports, one tool surface — stdio for local agents;
serve --http 8080speaks MCP Streamable HTTP (SSE responses for clients that ask, JSON otherwise) so a whole team shares one server, with optional bearer tokens - Several APIs, one MCP server —
[apis.NAME]sections in.mcpify.toml: per-API auth, caching, retries, filters and rate limits; collision-safe renames; aggregated health;mcpify statusprobes every API in parallel - Upstream courtesy built in — ETag-aware caching, idempotent-only retries (502/503/504),
--wait-on-429honors Retry-After,--rate-limit RPScaps requests/second (per upstream in multi-API, retries included) - Observability, opt-in only — Prometheus
--metrics(call counters, latencies, cache, health — plus projection/redaction counters when those run),--otelspans,--reloadhot swap,mcpify uilocal dashboard - Host it yourself for free — docker-compose with automatic-HTTPS Caddy plus a hardened systemd unit: Self-hosting guide
- Zero runtime dependencies — the entire tree is auditable stdlib Python; YAML specs need an optional
pip install 'mcpify[yaml]'
Quick start
# install (installs the `mcpify` command)
pipx install mcpify-openapi
# run without installing (uvx — pulls from PyPI on demand)
uvx --from mcpify-openapi mcpify list ./openapi.json --read-only
# first time? the wizard writes a config for you
uvx --from mcpify-openapi mcpify init
# ...as a container (GHCR, published on every release)
docker run -i ghcr.io/furkan708/mcpify:latest serve ./openapi.json --read-only
# ...or from source
git clone https://github.com/furkan708/mcpify.git
cd mcpify && pip install .
# 1. preview the tools that will be generated (add --cost for the context price)
mcpify list examples/petstore.json
# 2. validate the spec is agent-friendly (+ --probe for a live pre-flight)
mcpify doctor examples/petstore.json
# 3. serve it over MCP
mcpify serve examples/petstore.json --base-url https://petstore.example.com/v1
# 4. no agent client at hand? try the tools in your terminal
mcpify try examples/petstore.json --base-url https://petstore.example.com/v1
# 5. or share it over HTTP with the whole team
mcpify serve examples/petstore.json --http 8080 --http-token $SHARED_TOKEN
With authentication
# Bearer token read from the environment (never hardcoded)
export PETSTORE_KEY="sk-..."
mcpify serve petstore.json \
--base-url https://petstore.example.com/v1 \
--auth-env PETSTORE_KEY \
--auth-style bearer \ # optional: auto-detected from the spec
--read-only
No explicit style needed in the common case — the spec's security
declarations pick bearer/basic/header/query (with the right name) for
you. For HTTP Basic, the env variable holds username:password:
--auth-style basic --auth-env CREDS.
| Flag | Meaning |
|---|---|
--auth-env VAR |
environment variable holding the credential |
--auth-style bearer|basic|header|query |
how it is sent (default: auto-detected from the spec) |
--auth-name NAME |
header / query name for non-bearer styles (e.g. X-API-Key) |
With OAuth2 (client credentials)
For APIs behind an OAuth2 identity provider (RFC 6749 §4.4). Credentials
live in the environment; the access token is fetched, cached until its
expires_in, refreshed transparently, and re-fetched automatically once
if the API answers 401 mid-flight:
export OAUTH2_CLIENT_ID="..."
export OAUTH2_CLIENT_SECRET="..."
mcpify serve api.json \
--oauth2-token-url https://idp.example.com/oauth2/token \
--oauth2-client-id-env OAUTH2_CLIENT_ID \
--oauth2-client-secret-env OAUTH2_CLIENT_SECRET \
--oauth2-scope "read write" # optional; --oauth2-client-auth body for token endpoints that reject Basic
Split write identities too: --write-oauth2-token-url (+ client/scope
flags) runs a second client-credentials flow for non-GET calls — reads
authenticate as the read client, writes as the write client, each with
its own token cache and the same 401 self-heal. Mutually exclusive with
--write-auth-env (pick one credential kind for writes).
Multiple APIs in one server
Put several OpenAPI documents in one config and serve them as a single tool surface — no gateway, no per-API process:
# .mcpify.toml
[apis.catalog]
spec = "https://shop.example.com/openapi.json"
auth-env = "CATALOG_TOKEN" # per-API credential
cache-ttl = 60
rate-limit = 5 # per-API courtesy throttle (req/s)
redact = "password,client_secret" # per-API response masking
[apis.crm]
spec = "./crm.yaml"
read-only = true # per-API policy
base-url = "https://crm.internal/v2"
fields = "id,name" # per-API response projection
[apis.weather]
spec = "https://api.weather.gov/openapi.json"
timeout = 10
Surface switches (--lazy, --enable-preview, --http, --format) are
server-wide flags; credentials, policies, caching and retries are per-API.
mcpify list --cost # preview every API and price each surface
mcpify serve # stdio, all three APIs, prefixed on collisions
mcpify serve --http 8080
mcpify try # REPL across every API
mcpify status # probes each API concurrently
mcpify status reports per API — [catalog] reachable (status 200, 0.03s) — https://shop.example.com — 31 tools — and exits non-zero if any API is
unreachable. When two APIs expose the same tool name (list_pets), both
get renamed with their label (catalog_list_pets, crm_list_pets) so
nothing silently wins; non-conflicting names stay untouched. The
mcpify_health tool returns one report covering every API. Precedence
per key: CLI flags > [apis.NAME] > [serve]. Pass a positional spec
or [apis.*] sections — never both.
Plug it into your agent
Claude Code:
claude mcp add my-api -- mcpify serve openapi.json --read-only
Claude Desktop / Cursor / any MCP client (claude_desktop_config.json):
{
"mcpServers": {
"petstore": {
"command": "mcpify",
"args": ["serve", "~/specs/petstore.json", "--auth-env", "PETSTORE_KEY"]
}
}
}
HTTP transport (team-shared server) — run mcpify serve api.json --http 0.0.0.0:8080 --http-token $TOKEN once, then point HTTP-capable clients at it:
{
"mcpServers": {
"petstore": {
"type": "http",
"url": "http://your-host:8080",
"headers": { "Authorization": "Bearer <token>" }
}
}
}
Now ask your agent: "list the pets, then create one named Milo" — it discovers list_pets and create_pet, fills the arguments, and performs real HTTP calls.
How operations become tools
| OpenAPI | mcpify |
|---|---|
operationId |
tool name (sanitized; falls back to method_path) |
summary / description |
tool description the agent reads |
deprecated: true |
shown by mcpify list before you expose old endpoints |
parameters (path/query/header) |
individual typed arguments with enums |
requestBody (JSON) |
a body object argument |
$ref pointers |
resolved inline (components → real schemas) |
servers[0].url |
default base URL (override: --base-url) |
The agent only ever sees the tool list and your API's JSON responses — mcpify adds no middleware, caches nothing you did not ask for, and sends credentials nowhere except your API.
Doctor
$ mcpify doctor my-api.json
openapi: 3.0.3
title: Acme API
paths: 23
tools: 41 operations
servers: https://api.acme.com
warning: 12/41 operations have no operationId (names fall back to method_path)
warning: 30/41 operations have no summary (agents see no description)
Add --probe for a live pre-flight — after the static report, mcpify
dials one argument-free GET (or the base URL) and reports reachability;
a connection failure exits non-zero so CI and shell scripts stop before
serving:
$ mcpify doctor https://api.weather.gov/openapi.json --probe
...
probe: GET /alerts → 200 reachable (2.80s)
CLI reference
mcpify list <spec> [--tag T] [--include P] [--exclude P] [--read-only] [--json]
mcpify list --cost # price the surface (~4 chars/token)
mcpify list --cost --lazy # ...and the 3-meta-tool lazy surface
mcpify list --config .mcpify.toml --cost # multi-API: every surface priced
mcpify serve <spec> [--base-url URL] [--server INDEX|NAME] [--name N] [--auth-env VAR]
[--auth-style bearer|header|query] [--auth-name NAME]
[--oauth2-token-url URL --oauth2-client-id-env VAR
--oauth2-client-secret-env VAR] [--timeout S]
[--read-only] [--tag T] [--include P] [--exclude P]
[--http [HOST:]PORT] [--http-token TOKEN] [--wait-on-429 SEC]
mcpify try <spec> [same serve flags] # interactive REPL, no agent needed
mcpify output-server <spec> -o FILE [-- <any serve flags>]
mcpify ui <spec> [same serve flags] # local dashboard (tool explorer, health, config)
mcpify mock <spec> [--http 8000] [--delay-ms N]
mcpify diff OLD NEW [--json] [--fail-on-breaking] # upgrade report + CI gate
mcpify diff OLD NEW --probe [--auth-env V] # ...+ live check of the NEW API + cost delta
mcpify config-schema # JSON Schema for .mcpify.toml (editor wiring)
mcpify doctor <spec> [--probe --auth-env V --fail-on-http-error] # static audit + live pre-flight / CI gate
# token economics: --fields id,name (projection), --redact password,token (masking),
# --rate-limit RPS (upstream courtesy, retries included)
# credential split: --write-auth-env WRITE_KEY_ENV or --write-oauth2-token-url (reads keep --auth-env)
# tool-text overrides: [tool-text.TOOL] description = "..." in .mcpify.toml
# multi-API: define [apis.NAME] sections in .mcpify.toml, then run
# mcpify list|serve|try|status|ui (no positional spec) — one process, every API
# ops add-ons for serve/ui: --metrics [HOST:]PORT --reload --cache-warm
# --audit-log FILE --http-token-file FILE --plugin FILE (repeatable) --otel [ENDPOINT]
Notes & limitations
- JSON specs work out of the box; YAML specs need
pip install 'mcpify[yaml]' - External
$reftargets (files or URLs) are bundled automatically at load; circular cross-file refs are left in place rather than unwound (surface skips what it cannot resolve) - Oversized JSON responses truncate to valid JSON (first items + a truncation marker); non-JSON bodies cut at a character boundary
--fieldsselects at every level by documented rule (selected keys verbatim, non-selected containers transparent); it is a projection, not a security boundary — use--redactwhen a field must never reach the model- Request bodies are exposed as a single
bodyobject argument — predictable over clever - HTTP transport serves one JSON-RPC response per request (batching was removed from
the MCP spec); clients that send
Accept: text/event-streamget it framed as a single SSEmessageevent. Server-initiated streams (a GET stream with sessions) stay deliberately out of scope for a stateless server - Spec versions: OpenAPI 3.x and Swagger 2.x roots are accepted; 3.x is the happy path
Hardened against the real world
mcpify is audited on every release against a 10-category checklist of MCP best practices and published production failure modes — not just our own examples:
- Hostile-spec corpus (12/12): circular
$refs, multipart uploads,allOfschemas, server URL variables, relative base URLs, oversized responses — every scenario derived from a documented real-world failure, fixed, and locked in by a regression test. Sources include the arXiv study of REST→MCP generation across 18 real APIs. - Live integration: the real api.weather.gov spec loads in CI — and the live checks found the last two real bugs (nested-truncation envelope splits, top-level-only projection) before any user did.
- MCP lifecycle enforced: tools are unreachable until the client
completes the
initializehandshake. - Session survives upstream failures: a slow upstream (read timeout), a
mid-response disconnect, or even an unexpected exception inside one tool
becomes a clean
isErrortool result with remediation — never a dead stdio connection (the failure mode reported against other OpenAPI-to-MCP servers, replayed here and locked in by regression tests). - Blast-radius controls: read-only mode, deny/allow policy layer,
per-token RBAC, response projection + secret masking, rate limiting,
40k-char valid truncation,
--timeout, credentials never logged.
Full checklist with per-item status: docs/AUDIT-CHECKLIST.md
mcpify MCP 질문
mcpify MCP를 Claude Code에 추가하려면 어떻게 하나요?
터미널에서 claude mcp add mcpify -- uvx mcpify-openapi를 실행합니다. 모든 프로젝트에서 사용할 수 있게 하려면 --scope user를 추가합니다.
mcpify MCP를 Cursor에 추가하려면 어떻게 하나요?
~/.cursor/mcp.json를 열고 mcpServers 아래에 서버를 추가합니다. 위 설치 섹션에 표시된 Cursor 구성을 사용합니다.
OpenAPI 스펙을 어떻게 MCP server로 변환하나요?
mcpify serve <url-to-spec> 명령어를 사용하면 API를 즉시 MCP 도구로 서빙할 수 있습니다.
OAuth2와 같은 기존 인증 방식을 사용할 수 있나요?
네, OAuth2 client-credentials를 비롯하여 bearer, basic, header, query 인증 방식을 기본적으로 지원합니다.
AI가 민감한 정보를 보지 못하게 하려면 어떻게 해야 하나요?
--redact 플래그를 사용하여 API 응답에서 비밀번호나 토큰과 같은 특정 키를 마스킹함으로써 모델이 해당 정보를 보지 못하도록 설정할 수 있습니다.
여러 개의 API를 동시에 지원할 수 있나요?
네, 단일 .mcpify.toml 설정 파일에 여러 API를 정의하여 하나의 도구 인터페이스로 서빙할 수 있습니다.