Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Stops agents double-firing side effects: 1,000 racing duplicates, exactly one execution.
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이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
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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": {
"effectfence": {
"command": "npx",
"args": [
"-y",
"effectfence"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add effectfence -- npx -y effectfence프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"effectfence": {
"command": "npx",
"args": [
"-y",
"effectfence"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"effectfence": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"effectfence"
]
}
}
}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.
이 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 aurumflux20 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.
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(0.3.0)은 2개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js, Rust도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Toggl 2.0
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.
Toggl 2.0 MCP server for tasks, projects, time entries, and workspace operations.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Public register: the Retry-Safety Index lists which agent-payment implementations pay once when the answer is lost — verified safe, found & fixed (with time-to-fix), and how to get verified. Every row links to its proof.
Your swarm doesn't need more memory. It needs a causal fence around tool side effects.
Free: submit any client, facilitator, SDK or toolkit that moves money — yours or someone else's — and we read it and publish a verdict on the Retry-Safety Index at no cost. Findings come back with the mechanism, the file and line, and a failing test. You are counted, never named, until you ship a fix. [Submit for grading →](https://github.com/aurumflux20/hostile-facilitator/issues/new?template=submit.yml)
⚡ effectfence — THE STORM
1,000 attempts to charge order #777 ($49.00): concurrent racers + late retries…
ACTUAL EXECUTIONS : 1 ← the whole point served sealed receipt : 995 told to stand down : 4 elapsed : 22.33ms
💰 double-charges prevented this run: $48,951.00 ✅ ONE execution. Every other attempt was fenced, replayed, or refused.
Run the attack yourself:
cargo run --release --example storm
The storm above is one action, many racers. The harder case is *different* agents making *contradictory* decisions on the same production resource — the coordination failure now reported across production multi-agent systems (~a third of 2026 multi-agent incidents). Three autonomous SRE agents react to one latency spike:
cargo run --example turf_war
Agent A (autoscaler): scale node pool UP
ADMITTED. Fence leased cluster:prod-us-east-1 — executing kubectl scale up. DONE. EffectCert minted — verify() -> true
Agent B (cost-optimizer): scale the same pool DOWN REFUSED before kubectl ran: read-set for metrics:prod-us-east-1 is stale: B decided on seq 0, world is at seq 1.
Agent C (deploy-bot): roll the deployment BACK C's causal view is concurrent with A's: true -> escalated to a human instead of corrupting the cluster.
Actions proposed: 3 executed: 1 cluster: intended, not corrupted.
Each agent was individually correct for the state it read. Run concurrently without coordination, all three kubectl calls fire and the cluster ends in a state none of them intended — the $100M outage. The fence lets exactly one act, refuses the other two *before* their side effect runs, and tells each one why.
Nothing above is mocked — every call is the real crate API.
EffectFence is a causal concurrency fence for multi-agent tool calls. When more than one agent (or retry, or re-dispatch) can end up trying to run the same side-effecting operation — charge a card, send a payout, provision a resource — EffectFence guarantees exactly one attempt ever executes it: same-instant races are decided by an atomic compare-exchange reservation, and late duplicates get the recorded outcome replayed instead of running again. Every effect that does run gets a content-addressed certificate chained to whatever it was causally built on.
It ships as a Rust library (effectfence::fence) and as a stdio MCP server exposing three tools — fence_prepare, fence_commit, fence_abort — so agents can route side-effecting tool calls through the fence instead of racing each other directly.
In a multi-agent gateway, more than one caller can end up trying to run the same effect:
Naively, any of these double-runs the effect. Naively rejecting every duplicate with no memory of outcome is also wrong: if the first attempt crashed, the effect never runs at all, and a duplicate that arrives after success gets an error instead of the result it needs. EffectFence closes all of it with optimistic concurrency control (OCC) plus an intent ledger: attempts don't block each other, exactly one executes, and every other attempt learns what actually happened.
Four pieces compose into the fencing protocol:
The intent ledger is what stops *duplicates*, not just races. Every effect carries an intent — a stable id for the logical action (e.g. "charge:order-123"). Attempts sharing an intent are the same action: the first is admitted and holds a lease; concurrent duplicates are told an attempt is in flight; duplicates arriving after success get the recorded certificate replayed verbatim; duplicates after a failure are fenced (the side effect may or may not have fired — that must be reconciled, not blindly retried) until explicitly cleared. Crashed holders lose their lease after a TTL so the action isn't stuck forever.
Vector clocks (VectorClock) track causal "happened-before" relationships across agents — one logical counter per agent, joined via elementwise-max merge, compared via a le partial order, with a concurrent check for genuinely unordered events and a stable SHA-256 digest for inclusion in certificates.
OCC read-sets (ReadSetEntry) record the causal dependencies a decision was based on: "when I decided to act, domain D was at sequence S." Both prepare_effect_fence and commit_effect_cert validate every entry against live state — if anything moved, the attempt is rejected as stale rather than allowed to act on outdated information.
CAS domain fencing is where same-instant races are decided. Each domain (a named contention scope, e.g. "order:123") has an AtomicU64 sequence counter. The *decision* is a single atomic compare_exchange — exactly one concurrent caller can win for any given expected sequence. (Precision note: the counter *lookup* sits behind a short mutex; only the race decision itself is lock-free. Ideas for a fully lock-free path are welcome.)
┌ intent gate ──────── already done? → Replay(recorded cert) [do NOT run]
│ in flight / failed? → rejected [do NOT run] EffectRequest┤ ├ read-set check ───── dependency moved? → ReadSetStale [do NOT run] │ └ domain CAS ────────── lost the race? → DomainRace [do NOT run] │ └ Fresh(ticket) → run the effect → commit_effect_cert → EffectCert ↘ abort_effect (failed; fenced until reconciled)
Every committed effect becomes an EffectCert: a SHA-256 content hash over {intent, parent, domain, seq, tool, args, result, vector_clock, read_set, agent}, chained to a parent cert hash for causal lineage. Two certs with the same hash are, by definition, records of the same effect — EffectCert::verify() recomputes the hash and confirms it hasn't been tampered with or hand-built incorrectly.
This is a single-process fence with a durable ledger. Every admission, outcome and operator clear is appended to a JSON-lines file and fsync'd before the fence answers, so a restart of the proxy does not forget what already ran: a duplicate after the restart is replayed, not re-executed. Anything that was in flight when the process died is fenced as an unknown outcome on the next start — the holder is gone and nobody can say whether the effect fired — until an operator reconciles and clears it. (Library users: EffectFence::open(path, config); EffectFence::new() stays in-memory. The shipped binary picks $EFFECTFENCE_LEDGER, else ~/.local/state/effectfence/ .jsonl, and EFFECTFENCE_LEDGER=memory opts out.) Two things it deliberately does not do (yet):
SETNX+CAS in Redis, or an optimistic version column in Postgres) — the types here are meant to carry over directly to that backend.FenceConfig::lease_ttl (60 s by default). An effect that runs past its lease without saying anything therefore has its claim taken over and runs a second time, which is the very thing this crate exists to stop. The remedy is one call: EffectFence::heartbeat(intent) while the effect is still running (about every third of the lease). wrap does this for you on every forwarded call; agents driving fence_prepare directly should call the fence_heartbeat tool. Stop beating and the lease lapses on schedule, so a genuinely dead holder is still recovered.Memory is bounded: finished outcomes expire after a configurable TTL (FenceConfig::result_ttl, swept by EffectFence::sweep), queries never create tracking state, and domain counters are tiny and manually evictable (evict_domain).
use effectfence::fence::{
prepare_effect_fence, commit_effect_cert, Admission, EffectFence, EffectRequest, VectorClock, };
let fence = EffectFence::new();
let req = EffectRequest { intent: "charge:order-123".into(), // same action -> same intent, always parent: None, // hash of the cert this follows, if any domain: "order:123".into(), // contention scope tool: "charge_card".into(), args: serde_json::json!({"amount_cents": 1999}), read_set: vec![], // other domains this decision cross-checked agent: "agent-a".into(), known_clock: VectorClock::new(), };
match prepare_effect_fence(&fence, req)? { Admission::Fresh(prepared) => { // This attempt won. Actually run the charge... let cert = commit_effect_cert( &fence, prepared, serde_json::json!({"charge_id": "ch_123"}), )?; assert!(cert.verify()); // (on failure: abort_effect(&fence, prepared, "why") instead) } Admission::Replay(cert) => { // This exact action already ran -- use cert.result, charge nothing. } }
A concurrent duplicate of the same intent gets Err(FenceError::IntentInFlight); a same-instant race on the domain gets Err(FenceError::DomainRace); either way it must not run the effect.
cargo install effectfence # or: npx -y effectfence demo
effectfence demo
Twelve agents reach for one $49 charge at the same instant. You'll see it hit a built-in server raw — 12 duplicate charges — then the same twelve calls behind the fence: exactly 1. This binary is talking to itself, so no real call fires and you need no server of your own to see the point.
── Act 1: the raw server, no fence ──
DISTINCT effec
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