Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Drive devices and APIs from their W3C Thing Description. You gate every operation.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
THINGCTX_POLICY, THINGCTX_APPROVE_WHEN, THINGCTX_FS_ROOT필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"thingctx": {
"command": "uvx",
"args": [
"thingctx",
"--from",
"thingctx[mcp,http,mqtt,media,filesystem,authz]",
"thingctx-mcp",
"https://td.thingctx.com/index.json"
],
"env": {
"THINGCTX_POLICY": "your-value",
"THINGCTX_APPROVE_WHEN": "your-value",
"THINGCTX_FS_ROOT": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add thingctx --env THINGCTX_POLICY=your-value --env THINGCTX_APPROVE_WHEN=your-value --env THINGCTX_FS_ROOT=your-value -- uvx thingctx --from 'thingctx[mcp,http,mqtt,media,filesystem,authz]' thingctx-mcp https://td.thingctx.com/index.json실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"thingctx": {
"command": "uvx",
"args": [
"thingctx",
"--from",
"thingctx[mcp,http,mqtt,media,filesystem,authz]",
"thingctx-mcp",
"https://td.thingctx.com/index.json"
],
"env": {
"THINGCTX_POLICY": "your-value",
"THINGCTX_APPROVE_WHEN": "your-value",
"THINGCTX_FS_ROOT": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"thingctx": {
"type": "stdio",
"command": "uvx",
"args": [
"thingctx",
"--from",
"thingctx[mcp,http,mqtt,media,filesystem,authz]",
"thingctx-mcp",
"https://td.thingctx.com/index.json"
],
"env": {
"THINGCTX_POLICY": "your-value",
"THINGCTX_APPROVE_WHEN": "your-value",
"THINGCTX_FS_ROOT": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
THINGCTX_POLICY envTHINGCTX_APPROVE_WHEN envTHINGCTX_FS_ROOT env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 도메인 thingctx.com 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.2.2)은 3개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, 오늘냥이 (Oneul Nyangi)
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Real cat photos, diaries, profiles, age and food reference calculators, and breeds.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
thingctx turns a description of any API, device, or local process into tools an AI agent can call: authorized per operation, over the system's own transport, and the agent never holds your keys. The description is a W3C Web of Things Thing Description (a TD), a plain JSON file naming what the system can do. Write one, or compile it from an OpenAPI spec. The described system is the server, so you run no server per integration.
A "Thing" is whatever you want to describe: a REST API, an app, a sensor, a media server, a local object, or one system that is several of those at once. A media server takes commands over HTTP and serves its stream over RTSP. The pump in examples/ reads over MQTT and acts through a local call. Each is one Thing and one description.
A description names actions, properties, and events, and gives each one a form: the entry that says where and how to reach it. The URL scheme in that address picks the transport per call, so however many protocols one Thing spans, the agent still sees one tool set.
docs/BINDINGS.md covers the transports and how to add your own. A subprocess transport, exec, also ships, and it ships locked: it refuses every command until you hand it an explicit allowlist.
Those three stay distinct all the way to the call. A read, a write, and a subscribe do not collapse into one undifferentiated function, which is why the gate can allow the read and refuse the write on the same system. A flat list of functions has no such handle.
Pick your path: use it as a library if you own the agent loop, the command line if you do not want to write code, the MCP bridge if your host only speaks MCP, or add a transport if thingctx does not speak your protocol yet.
Stuck, or wondering whether something is possible? Ask in Discussions. Want to build something small? The open issues say what would help.
One paste shows the whole idea. The description is inline and the handler ships with the package, so nothing here needs a key, a network, or a second file:
pip install thingctx
import asyncio
import thingctx from thingctx.contrib.time import make_time_handler
TD = { "@context": "https://www.w3.org/2022/wot/td/v1.1", "id": "urn:thingctx:time", "title": "Time", "securityDefinitions": {"nosec_sc": {"scheme": "nosec"}}, "security": ["nosec_sc"], "actions": { "getCurrentTime": { "description": "Current time in an IANA timezone (default UTC).", "input": { "type": "object", "properties": {"timezone": {"type": "string"}}, }, "safe": True, "idempotent": True, "forms": [{"href": "local://getCurrentTime"}], } }, }
async def main(): client = thingctx.ThingClient(tds=[TD], bindings=[thingctx.LocalBinding(make_time_handler())]) tools, invoke = client.as_tools() # specs for your model; invoke runs a call print("tools:", t["function" for t in tools]) print(await invoke("time__getCurrentTime", {"timezone": "UTC"}))
asyncio.run(main())
tools: ['time__getCurrentTime'] {'timezone': 'UTC', 'datetime': '2026-07-26T15:59:03.233080+00:00', 'utc_offset': '+0000'}
That is the whole loop: a description in, tools out, calls routed. LocalBinding is a binding, a transport implementation; this one routes the local:// address to the handler you pass it. Every other transport works the same way; only the form's href changes.
pip install 'thingctx[llm,http,validate]'
Quote the argument; unquoted brackets fail in zsh. Base pip install thingctx has no dependencies; it already includes the local and exec transports. Redis support is pip install 'thingctx[redis]'. Every optional transport and capability has an extra, listed in pyproject.toml; each one this page uses is named next to the code that needs it.
A description can be small. This one drives the live, key free Open-Meteo forecast API, so it runs as written. Save it as weather.td.json, a later example uses it:
{
"@context": "https://www.w3.org/2022/wot/td/v1.1", "id": "urn:example:weather:v1", "title": "Weather", "securityDefinitions": { "nosec_sc": { "scheme": "nosec" } }, "security": ["nosec_sc"], "actions": { "forecast": { "input": { "type": "object", "properties": { "latitude": { "type": "number" }, "longitude": { "type": "number" }, "current": { "type": "string" } }, "required": ["latitude", "longitude"] }, "forms": [{ "href": "https://api.open-meteo.com/v1/forecast", "htv:methodName": "GET" }] } } }
thingctx projects each action to a tool named __ : this file yields weather__forecast (a version segment on the id is dropped). docs/MAPPING.md specifies the full projection. The description carries no secrets, so it is safe to commit and share. The secret is supplied at runtime to the binding that carries the call. Secrets are keyed per Thing.
If your system already has an OpenAPI 3.x spec, you do not have to author a description at all:
pip install 'thingctx[openapi]'
thingctx import openapi https://api.example.com/openapi.json --out api.td.json
The spec can be a file or a URL, JSON or YAML; --base-url, --id, and --title override what the spec says. The result is a normal description, so everything else here applies to it unchanged.
Ready made descriptions for common apps, developer tools, and devices live at td.thingctx.com.
Own the agent loop? Read descriptions, hand the specs to your model, and route each call back through invoke. ThingClient needs no LLM and has no opinion on what chose the action; any code can drive it. This sketch shows the surface against a folder describing a pump; from_arg turns a path or URL into a registry of descriptions:
import thingctx
async def run(): # a sketch, not a program: call it from your own loop client = thingctx.ThingClient.from_registry(thingctx.from_arg("./descriptions/")) specs, invoke = client.as_tools()
await invoke("pump__set_speed", {"rpm": 1500}) await client.read_property("pump__rpm") await client.write_property("pump__target_rpm", 1500) # gated like invoke async for evt in await client.subscribe( "pump__overheat" ): # subscribe returns an async iterator ...
The form picks the transport per call, so one client can read over HTTP, subscribe over MQTT, and read or write cached properties over Redis. Bindings that pull optional dependencies, including MQTT and Redis, are off by default: install the extra and pass bindings=thingctx.BindingRegistry.default(mqtt=True, redis=True).
Want the loop handled for you? The llm extra runs any provider through litellm; add the http extra, since the weather file's form is HTTPS. Set your provider key in its usual variable (OPENAI_API_KEY, ANTHROPIC_API_KEY, and so on) and pick a model with THINGCTX_MODEL:
import asyncio
import thingctx
async def main():
host = thingctx.from_file("weather.td.json") print(await host.chat("What is the forecast for Cairo? Latitude 30.0, longitude 31.2."))
asyncio.run(main())
The model calls weather__forecast itself and answers in prose:
The forecast for Cairo is clear, around 34 C.
Two opt in layers stand between an agent and a real system; both run before any transport is selected. Neither layer handles a credential. The binding holds the secret and the model never sees it.
Approval gates risky calls behind a human. Risk is read from the description, and when to gate is yours: declared (only actions the description marks risky; the default), destructive (adds non idempotent actions and every property write), all, or never. A gated call with no approver is denied: a gate with nobody to open it stays shut. The check sits inside invoke and write_property, so it covers the LLM loop, direct callers, and the MCP bridge alike.
Carrying on from the first example above, with the same TD:
def approve(req): # sync or async; return True to allow
return input(f"run {req.tool_name}{req.arguments}? [y/N] ").lower() == "y"
client = thingctx.ThingClient( tds=[TD], bindings=[thingctx.LocalBinding(make_time_handler())], approve=approve, approve_when="all", )
Authorization decides from policy, per caller, per operation. Pass a pdp and an identity and every call authorizes the resolved (thing, affordance, operation) before it reaches the system; an affordance is an action, property, or event named in the description. This snippet condenses examples/14_authz.py, which runs as is on the core install. It defines the TD and Pump used below: a pump with one property, target_rpm.
from thingctx import LocalBinding, ThingClient
from thingctx.authz import LocalPolicyGrantSource, PolicyDecisionPoint, build_vocabulary
reader = ThingClient( tds=[TD], bindings=[LocalBinding(Pump())] ) # no pdp yet; parsed only to read the description vocab = build_vocabulary(reader.things) # the closed set the description declares
grants = LocalPolicyGrantSource({"operator": {("urn:demo:pump", "target_rpm", "readproperty")}}) pdp = PolicyDecisionPoint(vocabulary=vocab, grant_source=grants) identity = {"sub": "alice", "roles": ["operator"]} # claims, validated upstream
client = ThingClient(tds=[TD], bindings=[LocalBinding(Pump())], pdp=pdp, identity=identity)
Alice's operator role grants read on target_rpm and nothing else, so her reads pass and her writes are refused. The vocabulary is closed: a grant is honored only for operations the description declares. thingctx.authz imports no crypto and runs on the dependency free core. Identity is claims that something upstream validated, never the credential itself.
Running the example prints:
vocabulary (grantable tuples the TD declares):
(urn:demo:pump, target_rpm, readproperty) (urn:demo:pump, target_rpm, writeproperty)
READ target_rpm -> ALLOWED, device returned 1200 WRITE target_rpm -> DENIED, grant does not include ('urn:demo:pump', 'target_rpm', 'writeproperty')
RE-READ target_rpm -> 1200 (unchanged: the denied write never ran)
The full model is in docs/SECURITY.md.
Some agents only take tools over MCP. For those, thingctx ships one generic MCP server, with no per integration server. It serves any registry of descriptions: a folder, a URL, or a W3C Thing Description Directory. A Directory is the standard catalog server for descriptions.
pip install 'thingctx[mcp,http]'
thingctx-mcp ./descriptions/
For Claude D
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요