Converts any OpenAPI REST API into a production-ready MCP server for use with AI clients like Claude Code and Cursor.
Also known as furkan708/mcpify, mcpify-openapi
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- Tools
- —
- Downloads, 30 days
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- Latest version
- 1.19.0
- Last commit
- Sep 4, 2026
- License
- MIT
What is mcpify MCP?
mcpify converts any OpenAPI REST API into a production-ready MCP server for use with AI clients like Claude Code and Cursor.
Summary generated from the project's README
About mcpify MCP server
Developers can transform any OpenAPI 3.x REST API into a functional MCP server to enable direct interaction from AI clients like Claude Code and Cursor. By pointing the command line interface at a specification file or URL, every API operation is automatically converted into a first-class tool that the agent can discover and execute. This process is designed to be fast, requiring only a single command to bridge the gap between standard web services and model context protocols.
Security and efficiency are central to the implementation. Users can manage credentials through environment variables to ensure secrets never touch the model, and can implement strict policies like read-only access or secret masking using the redact flag. The server supports both local stdio transport and remote HTTP/SSE connections for team-wide deployment. It also includes specialized features for managing token usage, such as response projection to select specific fields and lazy loading to reduce the context budget sent to the AI.
What you can do with it
- 1Secure API access for agentsRestrict an AI agent to read-only operations to prevent accidental data mutation during a session.
- 2Manage multiple APIs simultaneouslyCombine several different OpenAPI documents into a single MCP server instance with unified health monitoring.
Written from the project's README. Every use case is checked against a quote from it.
How to install mcpify MCP
Formats verified 10 Nov 2026Add to CursorAdd to GooseInstall mcpify MCP in Claude Code
$ claude mcp add mcpify -- uvx mcpify-openapiInstall mcpify MCP in Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"mcpify": {
"command": "uvx",
"args": [
"mcpify-openapi"
]
}
}
}Install mcpify MCP in VS Code
.vscode/mcp.json
{
"servers": {
"mcpify": {
"type": "stdio",
"command": "uvx",
"args": [
"mcpify-openapi"
]
}
}
}Install mcpify MCP in VS Code CLI
$ code --add-mcp '{"name":"mcpify","type":"stdio","command":"uvx","args":["mcpify-openapi"]}'Install mcpify MCP in Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"mcpify": {
"command": "uvx",
"args": [
"mcpify-openapi"
]
}
}
}Install mcpify MCP in Codex
$ codex mcp add mcpify -- uvx mcpify-openapiInstall mcpify MCP in Codex config.toml
~/.codex/config.toml
[mcp_servers.mcpify] command = "uvx" args = ["mcpify-openapi"]
Install mcpify MCP in Gemini CLI
$ gemini mcp add -s user mcpify uvx -- mcpify-openapiInstall mcpify MCP in Gemini settings.json
~/.gemini/settings.json
{
"mcpServers": {
"mcpify": {
"command": "uvx",
"args": [
"mcpify-openapi"
]
}
}
}Configuration
OAUTH2_CLIENT_IDOAUTH2_CLIENT_SECRETPETSTORE_KEY
| Name | Description | |
|---|---|---|
| OAUTH2_CLIENT_ID | — | |
| OAUTH2_CLIENT_SECRET | — | |
| PETSTORE_KEY | — |
Automated checks
Ran Nov 14, 2026Full report →Passed our automated checks. That is not a security audit: read the code and give the server the narrowest access it needs. How checks work
- Source repository linked and reachablefurkan708/mcpify is public and reachablegithub.com/furkan708/mcpify ↗Pass
- Package names this repository as its sourceNot checked
- Build provenance (Sigstore attestation)Sigstore attestation for mcpify-openapipypi.org/project/mcpify-openapi/ ↗Pass
- Open source license (OSI)MITspdx.org/licenses/MIT.html ↗Pass
- Commit or release in the last yearLast commit or release 2026-09-04github.com/furkan708/mcpify ↗Pass
- OpenSSF ScorecardNot checked
- Package name not close to a popular packageNo popular package one edit away from mcpify-openapiPass
- No critical advisory in the package or its dependencies1 resolved dependencies checked; no critical advisoryosv.dev ↗Pass
- No hidden instructions to the model0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersPass
- Destructive tools are labelledNot checked
- Remote endpoint answers the MCP handshakeNot checked
README
View on GitHubmcpify
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 questions
How do I add mcpify MCP to Claude Code?
Run claude mcp add mcpify -- uvx mcpify-openapi in your terminal. Add --scope user to make it available in every project.
How do I add mcpify MCP to Cursor?
Open ~/.cursor/mcp.json and add the server under mcpServers, using the Cursor config shown in the install section above.
How do I turn an OpenAPI spec into an MCP server?
You can use the command mcpify serve <url-to-spec> to immediately start serving the API as MCP tools.
Can I use this with existing authentication like OAuth2?
Yes, it has built-in support for OAuth2 client-credentials, as well as bearer, basic, header, and query authentication styles.
How can I prevent the AI from seeing sensitive information?
You can use the --redact flag to mask specific keys like passwords or tokens in API responses so the model never sees them.
Does it support multiple APIs at once?
Yes, you can define several APIs in a single .mcpify.toml configuration file to serve them as a single tool surface.