Mirobody
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
제작자가 쓴 설명(영어 원문)
Read-only MCP server for coding-agent traces, alerts, costs, usage, and budget health.
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.
AGENTGUARD_API_KEY, AGENTGUARD_URL비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 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": {
"agentguard47": {
"command": "npx",
"args": [
"-y",
"@agentguard47/mcp-server"
],
"env": {
"AGENTGUARD_API_KEY": "your-value",
"AGENTGUARD_URL": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add agentguard47 --env AGENTGUARD_API_KEY=your-value --env AGENTGUARD_URL=your-value -- npx -y @agentguard47/mcp-server실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"agentguard47": {
"command": "npx",
"args": [
"-y",
"@agentguard47/mcp-server"
],
"env": {
"AGENTGUARD_API_KEY": "your-value",
"AGENTGUARD_URL": "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": {
"agentguard47": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@agentguard47/mcp-server"
],
"env": {
"AGENTGUARD_API_KEY": "your-value",
"AGENTGUARD_URL": "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.
AGENTGUARD_URL 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 GitHub 계정 bmdhodl 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
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.
입력해야 할 값: AGENTGUARD_API_KEY
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 5개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Mirobody, FHIR MCP Server, Google Health MCP
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications
Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Stop runaway agents with runtime checks in Python.
AgentGuard checks budgets, repeated tool calls, retries, and elapsed time in instrumented Python code. Guards raise exceptions so your application can stop the next operation. The base SDK has no runtime dependencies and needs no account.
Names: this repository is agent47, the PyPI package is agentguard47, and the Python import is agentguard. AgentGuard 2.0.0 requires Python 3.11 or newer. On Python 3.9 or 3.10, pin agentguard47==1.4.0. See the Python migration guide before upgrading.
Install in a virtual environment, then run the offline checks:
python -m pip install agentguard47
agentguard doctor agentguard demo
doctor checks the installation and local trace writing. demo exercises budget, loop, and retry stops without provider keys or network access. Follow the trace path printed by the command to inspect its output. agentguard demo --feedback prints a local redacted report; nothing is sent.
For a fresh PowerShell install and a runnable raw starter, follow the published-release walkthrough.
agentguard receipt agentguard_demo_traces.jsonl prints a receipt of each stop with the trace's SHA-256 drawn as a barcode. Add --format markdown to paste it into a PR or issue. The hash identifies the trace file; it is not a signature. This stop receipt records a covered guard refusal. Anthropic's official /receipts plugin summarizes past Claude Code work (30 days by default). Neither output proves prevented spend or provides a signed attestation. The agentguard receipt command stays the same.
agentguard hook claude-code --install --write
This installs a Claude Code hook that refuses the third identical tool call in a row and a call that already failed twice. "Identical" ignores JSON key order and preserves case and whitespace in values. The optional no_progress_max rule refuses a tool after repeated empty or same-error results even when input changes; it is off by default. Refusals omit raw input and go to .agentguard/claude-code/trace.jsonl. It checks tool calls, not tokens or subscription quota. See the Claude Code hook guide.
agentguard run --budget-usd 5 agent.py
This patches the OpenAI and Anthropic clients, then runs agent.py in the same interpreter. Settings come from flags, then environment variables, then .agentguard.json. A guard stop exits 1. Every run ends with the trace path on stderr, ready for agentguard receipt. agentguard run python -m mypkg works too. The bounds are the same as patching the client yourself; see enforcement boundary.
Subprocesses start a separate interpreter and are not patched by the parent. A detached, uninstrumented child can keep running after the guarded script exits. The offline reproduction demonstrates that boundary with two simulated calls and no network access.
agentguard run prices every patched call at paid rates, including a local model behind an OpenAI-compatible URL such as Ollama. A dollar budget can then stop a model that costs nothing. For a local model, patch the client in the script with free_local_clients=[client] and a BudgetGuard token or call cap, then run the script with python; see free local clients.
Save this as budget_demo.py and run python budget_demo.py. It makes no network requests.
from agentguard import BudgetExceeded, BudgetGuard
budget = BudgetGuard(max_calls=2) completed = 0
for _ in range(3): try: budget.check() # Check before the operation.
completed += 1 budget.consume(calls=1) # Record the completed operation. except BudgetExceeded: print(f"Stopped before call {completed + 1}")
assert completed == 2
Expected output: Stopped before call 3.
A stuck agent often rewords each retry, so no call repeats exactly. max_no_progress counts results instead: the same tool coming back empty, or with the same error, N times in a row stops the run whatever the arguments. normalize=True canonicalizes containers while preserving case and whitespace in argument values. Both options are off by default.
from agentguard import LoopDetected, LoopGuard
loop = LoopGuard(normalize=True, max_no_progress=3)
for pattern in ["retry_count", "retryCount", "retries"]: loop.check("grep", {"pattern": pattern}) matches = [] # Put your search here. This one finds nothing. try: loop.record_result("grep", matches, tool_args={"pattern": pattern}) except LoopDetected as stop: print(stop)
Expected output: No progress: grep came back empty 3 times in a row (limit: 3). Change the approach instead of rewording the call. Functions wrapped with trace_tool feed results to the guard automatically. Any other result in between starts the count over, so pagination and edit-then-test cycles do not trip it.
Install the provider's client separately. For OpenAI:
python -m pip install openai
from agentguard import BudgetGuard, JsonlFileSink, Tracer, patch_openai
budget = BudgetGuard(max_cost_usd=5.00) tracer = Tracer( service="my-agent", sink=JsonlFileSink(".agentguard/traces.jsonl"), ) patch_openai(tracer, budget_guard=budget)
Standard OpenAI clients created earlier are covered too, including resource objects obtained before the patch. Activate the patch before sending requests or saving bound methods and raw/streaming response helpers. Those saved references can retain the original callable; recreate them after activation. patch_openai_async() covers async clients, and agentguard.init() enables both. See the enforcement boundary.
The patch checks recorded usage before dispatch and records response usage afterward, including streamed calls once the final usage arrives. A response can exceed the remaining cost or token allowance. Concurrent requests do not reserve capacity. Chat Completions streams request include_usage unless the caller already set it.
The OpenAI Agents SDK runs on responses.create, so agentguard.init() before the Runner puts every model call under the budget (example). Hosted tools and background=True responses are not covered. See the getting started guide for setup, traces, and framework starters.
flowchart TD
accTitle: AgentGuard operation checks accDescr: Check a limit before an operation, then record usage. A[Instrumented operation] --> B{Guard check} B -->|Limit reached| C[Raise exception] B -->|Allowed| D[Run operation] D --> E[Record usage and trace] E --> A
Text equivalent: check before an operation, run it if allowed, then record usage. A guard exception returns control to your application's error handler.
| Guard | Checks | Raises |
|---|---|---|
BudgetGuard | Recorded calls, tokens, or estimated cost | BudgetExceeded |
LoopGuard | Repeated tool calls; opt in to normalize=True and max_no_progress=N for reworded ones | LoopDetected |
FuzzyLoopGuard | Tool frequency and alternating patterns | LoopDetected |
RetryGuard | Retries per tool | RetryLimitExceeded |
TimeoutGuard | Elapsed time when checked | TimeoutExceeded |
RateLimitGuard | Calls within a sliding minute | BudgetExceeded |
X402SpendGuard | Payment amounts before the payment callback | BudgetExceeded |
For task budgets, use BudgetGuard.goal(...). For signatures and defaults, read the guard source and public exports.
Budgets can also persist across runs: configure JsonFileStateStore, a shared key, and period="day" for a daily counter. Set warn_at_pct=0.8 and an on_warning callback for an 80% warning. Workers must explicitly share the store and key; child-agent budget inheritance is not automatic. Monthly SDK limits are not implemented. See the capability matrix.
[crewai] extra pulls ChromaDB. The 2026-09-12 audit found four unresolved advisories, including PYSEC-2026-311 / CVE-2026-45829. Review that exposure before installing the extra. Base SDK installs do not include ChromaDB.See security reporting, the dated dependency audit, and release notes. Audit results describe their recorded date, not a permanent clean bill of health.
The SDK is the free local proof path. Start local. Add hosted ingest only when you need retained history, alerts, team visibility, spend trends, hosted decision history, or dashboard-managed remote kill signals.
Local guards remain authoritative. HttpSink mirrors trace and decision events; it does not execute remote kill signals by itself. See the dashboard contract before configuring it.
Local use has no hosted event quota, retention period, or API-key allocation. Network egress requires an integration you configure, such as HttpSink or an OpenTelemetry exporter.
Nothing in the local SDK phones home. The AgentGuard website describes the optional hosted service.
| You want to | Start here |
|---|---|
| See which paths actually stop a call | Enforcement boundary |
| Install and trace a first run | Getting started |
| Find guides and source references | [Do
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요