Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Snapshot tests and CI for agent workflows: record a run, replay it at 0 tokens, diff for drift.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"reelier": {
"command": "npx",
"args": [
"-y",
"reelier",
"serve"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add reelier -- npx -y reelier serveIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"reelier": {
"command": "npx",
"args": [
"-y",
"reelier",
"serve"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"reelier": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"reelier",
"serve"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto seldonframe bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.24.0) kam vor 3 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, yontu
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Türkçe yazı denetimi: TDK kuralları, yapay zekâ izleri, metin türüne göre üslup.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
*Your agents worked all night. Here's exactly what changed.*
Reelier records the run that worked, freezes it as a replayable skill, and replays it deterministically — every run comes back as a receipt: proof of what the agent did and what changed because of it. Agents make claims. Reelier writes receipts.
[Website](https://www.reelier.com) · [Docs](https://www.reelier.com/docs) · [SPEC.md](./SPEC.md)
▶ watch with sound (27s)
Agent-authored PRs (Dependabot, Claude, Codex, Cursor, …) get a receipt comment in seconds: author, files changed, declared scope vs. what actually changed, sensitive paths flagged. No workflow file, no CLI, no config.
[→ Install the Reelier receipts GitHub App](https://github.com/apps/reelier-receipts) — free on public repos, forever.
Reelier receipt — agent PR
Author:
dependabot[bot]· Files changed: 2 (+119 −41)
Declared scope: none (add
.reelier/scope.ymlto enable unexpected-write detection)
Sensitive paths touched: ⚠ 1 —
package-lock.json
Proves scope and change, not correctness
A real receipt from Reelier's own repos — see one live. Declare scope per agent in .reelier/scope.yml (or a reelier-scope block in the PR body) and the receipt reports unexpected writes. The receipt proves scope and change, never correctness or safety.
AI agents are non-deterministic — the same prompt, a different result every run — and they'll claim they did the work whether they did or not. Reelier records the run that worked, replays it deterministically, and writes a signed receipt that proves it. Point it at your existing CI in one workflow — it adds a verifiable receipt, it doesn't replace your stack.
Measured on a real head-to-head benchmark, same task, same data (full method):
Deterministic replay is also ~50× cheaper and ~59× faster than re-running the agent, on the same benchmark.
npm i -g reelier && reelier init
# No Node install needed — same commands via Docker:
docker run --rm ghcr.io/seldonframe/reelier --help
reelier init [--dry-run] performs one checkpointed local inspection across all three Reelier paths: Path A observation coverage, Path B replay/freeze candidates, and Path C boundable/outcome-capable/shadow-only/unsupported connections and candidates. It does not deploy, gate, dispatch, upload, copy credentials, or rewrite host configuration. --dry-run writes nothing; the normal command writes only sanitized artifacts below .reelier/init/.
Teach your coding agent when to reach for Reelier. Same two commands, either host:
claude plugin marketplace add seldonframe/reelier
claude plugin install reelier@seldonframe
codex plugin marketplace add seldonframe/reelier
codex plugin add reelier@seldonframe
This installs two Agent Skills and nothing else. reelier-replay teaches your agent to freeze a repeatable tool-call job and replay it at 0 tokens. reelier-write-safety covers bounding an agent's writes before you grant them: what the recorder sees, what a policy refuses, and what a receipt does and does not prove. It ships no MCP servers, so it does not wrap, observe, or gate any tool call on its own; the reelier CLI does that, and the skills drive it via npx. Packaged in both the Agent Plugins v1.0.0 format (plugin/agent-plugins/) and the Claude Code format (plugin/claude/), generated from one source by scripts/build-plugin-packages.mjs.
Verified end to end on codex-cli 0.147.0-alpha.1.2: both formats install, enable, and the skill reaches the model. Other hosts are untested, and per-host status is tracked in docs/specs/agent-plugins-coverage-v1.md §4 rather than claimed here.
reelier init --dry-run # inspect Path A/B/C locally; write nothing
reelier init # persist resumable sanitized inspection artifacts reelier run .skill.md # replay deterministically — 0 tokens (read-only by default) reelier diff # SAME or DRIFTED, per step — exit 1 on drift reelier push .skill.md # sync receipts to your ledger (opt-in) reelier ci # write a workflow: drift-CI + PR receipts, one command
reelier init reveals observed coverage and local candidates without changing routes. reelier mcp --wrap " " proxies live tools; reelier scan/from-session freezes supported history.reelier compile turns a trace into a SKILL.md — 0 LLM calls, minimal assertions, honest gaps printed as Open questions.reelier run replays it at Level 0 — no LLM, byte-identical, read-only by default (writes need --allow-writes).reelier diff reports SAME or DRIFTED per step, with the failing assertion as the *why* — exit 1 on drift.reelier login connects this machine to Reelier Cloud with a device code in your browser — or set REELIER_CLOUD_URL/REELIER_CLOUD_KEY for CI and self-hosting.reelier push optionally syncs it to a ledger for a permalink and an embeddable verified-replay badge.Already have an Agent Skill? Convert it — your skill, minus the model:
reelier compile trace.jsonl --from-skill ./my-skill/SKILL.md
| Test | Command | Answers |
|---|---|---|
| Determinism | reelier run | *Does this still do what it did?* |
| Recovery | reelier run --fail N | *If this broke, would the skill notice and heal?* |
| Drift | reelier run --wrap " " | *Has the world moved out from under this skill?* |
*Taxonomy due to Mads Hansen's review of the launch post.* Full semantics for each test, including recovery injection and manifest guardrails: docs/REFERENCE.md.
Dependabot and Renovate open the PR and run your test suite — but neither knows what your agent actually *does* at runtime, so a dependency bump that silently changes a tool call's shape (a renamed field, a new default, a different error) sails through with green unit tests. This is the check they don't run.
Copy .github/workflows/reelier-bump-check.yml into your repo, point skill: at your own recorded .skill.md file(s), and it will: gate to PRs from dependabot[bot]/renovate[bot] (or a dependencies label), install the bumped dependency, replay your recorded skill live against it at --max-level 0 (0 tokens), and fail the check on the exact step that drifted.
This tests dependency and MCP-tool-call behavior — it does not test model upgrades; --max-level 0 never calls an LLM. Full listing copy and setup: docs/marketplace-listing.md.
A pushed receipt carries a ladder of independently-verifiable claims — not one blanket "verified." Depending on what you turn on, it can be signed, timestamped, CI-attested, and carry cross-checkable provider request-ids. reelier verify recomputes every claim offline, and a claim you haven't enabled just renders as an honest gap, never a shamed one.
See a real one: reelier.com/r/HWBdmGob9KeHRqXi-OEaRD0z.
Full 8-rung ladder, what each rung does and doesn't prove: docs/REFERENCE.md.
| Employee lifecycle | Reelier equivalent |
|---|---|
| Skillify a session | reelier from-session |
| Performance review | reelier run + reelier diff |
| Fleet maintenance | scheduled replays + drift alerts |
| The record | signed receipts |
"Verified" describes the record, never the agent — a receipt proves what ran and what changed, not that the agent was good at its job.
An employment contract doesn't make an employee good — it makes what they did visible and bounded. Same here: receipts prove scope and change, never correctness.
MIT, free forever (versions ≤0.16.0 remain AGPL-3.0). Your data — skills, traces, runs — is specified in SPEC.md, so leaving is copying a folder.
Contributing: issues and PRs welcome — SPEC.md is the source of truth for formats; fix the code, not the spec. npm test before a PR.
If Reelier saved you a re-run, [star it](https://github.com/seldonframe/reelier) ⭐ — it's how other builders find it.