Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Contextual blast-radius scoring for shell commands an AI agent is about to run
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"blast-scope": {
"command": "uvx",
"args": [
"blast-scope"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add blast-scope -- uvx blast-scopePégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"blast-scope": {
"command": "uvx",
"args": [
"blast-scope"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"blast-scope": {
"type": "stdio",
"command": "uvx",
"args": [
"blast-scope"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub Atharva-Jayappa, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.6.1) llegó al registro hace 3 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, TF Rooms
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Live room availability, rates and stay quotes for 12 New Leaf motels in Twin Falls, Idaho.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
A consequence engine for shell commands. Blast Scope scores what a command would actually *do* — before an AI agent (or you) runs it. It doesn't pattern-match syntax into a blocklist; it figures out the command's real target, observes that target with a safe, read-only probe, and returns a structured risk score with evidence.
The whole point is *contextual* blast radius. The same command gets a completely different score depending on what it would actually hit:
COMMAND SEVERITY WHY ADVICE
───────────────────────────────── ──────── ────────────────────────────────────────── ─────── rm -rf ./logs LOW 0 importers · regenerable · outside src proceed rm -rf ./config CRITICAL 8 modules import it · high PageRank hub block git reset --hard (clean tree) LOW nothing uncommitted to discard proceed git reset --hard (4 dirty files) HIGH would throw away 4 files of uncommitted work confirm git push --force (protected) CRITICAL would orphan commits on a protected branch block docker volume rm cache (absent) LOW volume doesn't exist — nothing to remove proceed docker volume rm pgdata (in use) CRITICAL holds data · in use · no image to rebuild block pip uninstall flask (uv.lock) LOW regenerable — exact version pinned in lock proceed DROP TABLE users (42 rows) CRITICAL schema + 42 rows · irreversible block DELETE FROM logs (in txn) HIGH no WHERE — but inside a txn, ROLLBACK-able confirm
Two commands can be byte-identical and score four bands apart. That gap is the product.
Not a blocklist. Not a replacement for Shellfirm. Not a syscall monitor. It
scores *structural consequence* — advisory, never blocking — and for the rare
critical command it captures an undo snapshot first.
A command flows through a cheap funnel: almost everything is recognized as non-destructive in microseconds and exits silent. Only a flagged *destructive candidate* pays for a probe.
shell command
│ split chains (&& || ; |) · de-alias PowerShell · parse flags/targets ▼ ┌──────────────────────────────────────────────────────────────────────┐ │ STAGE 1 · triage (near-free regex — runs on every command) │ │ which class? git · docker · pip/uv · sql · else filesystem │ │ destructive? git status → no. git reset --hard → yes ↓ │ └───────────────────────────────┬──────────────────────────────────────┘ destructive candidate │ (everything else exits here, silent) ▼ ┌──────────────────────────────────────────────────────────────────────┐ │ ELIGIBILITY FILTER safe read-only probe? AND undo authorable? │ └──────────────┬──────────────────────────────────────┬─────────────────┘ yes, probe it │ no probe here / now │ ▼ ▼ STAGE 2 · safe probe (read-only) heuristic estimate git status · reflog · rev-list from a static per-class docker inspect · ps · ls table — and LABELED sqlite SELECT count(*) [mode=ro] "(estimated)" so you pip/uv read lockfiles know it wasn't probed │ │ └─────────────────────┬─────────────────────┘ ▼ blast radius × reversibility (combined PER CLASS — no global formula) filesystem also folds in: dependency-graph centrality + recoverability ▼ score 0.0–1.0 → severity (low / medium / high / critical) ▼ PreToolUse hook: silent (low/med) · advise (high) · advise + snapshot (critical)
The eligibility filter is the design boundary. A command class earns a *live probe* only when both hold: (1) its impact is observable by a strictly side-effect-free read (HTTP-GET sense — never mutate state to assess state), and (2) its undo story is well-known enough to encode in a static table. When a probe can't run here and now (no docker daemon, no DB driver, no creds), the tool degrades to a labeled estimate — it never guesses silently, and it never blocks.
See docs/heuristics.md for the per-class tables, the exact filesystem formula, and calibration.
| Class | Destructive ops it scores | Safe (read-only) probe | Reversibility signal |
|---|---|---|---|
| Filesystem | rm -rf, mv, > truncate | dependency graph + git status | git-tracked? regenerable? secret? precious? |
| Git | reset --hard, push --force, branch -D, clean -fdx | status · reflog · rev-list · rev-parse @{u} | reflog window · remote ahead · protected branch |
| Docker | volume rm, system prune -a, rm -f | volume inspect · ps -a · volume ls | volume → none · container → recreatable from image |
| pip / uv | pip uninstall, uv pip uninstall | read lockfile / manifest (no subprocess) | lockfile present → fully regenerable |
| SQL | DROP, TRUNCATE, DELETE without WHERE | SQLite: SELECT count(*) mode=ro; transaction check | inside a transaction? backup posture? |
New classes drop in behind one protocol (triage / assess) in src/blast_scope/classes/; each class confines assess to strictly side-effect-free reads.
Calibrated multi-class guardrail with command resolution and a precise dependency graph.
| Capability | Module |
|---|---|
| Flag/operand-sensitive command model (POSIX and PowerShell) | command_effects.py, command_parser.py |
Command resolution — env/tilde/brace/glob expansion, unset-var hazards, script transparency (sh -c, npm run + pre/post hooks, script files, Makefile targets), read-only $(...) substitution | resolution.py |
Dry-run oracles — git clean -n exact lists, reset divergence, checkout clobber preview, find -delete→-print rewrite, sqlite scoped-DELETE counts, rsync --dry-run; oracle targets feed the undo snapshot | classes/git.py, classes/find.py, classes/rsync.py, classes/sql.py |
| Recoverability classification (git state, secrets, regenerable, precious data) | recoverability.py |
| Dependency graph + weighted PageRank centrality, incremental indexing | graph_resolver.py, centrality.py |
| Two-axis, evidence-based filesystem scoring | risk_scorer.py |
| Command-class probes — git / docker / pip·uv / SQL, behind one protocol | classes/ |
| Out-of-graph path analyzers (infra / config-by-path) + git base | consequences.py, vcs.py, infra.py, config_refs.py |
| PreToolUse hook + tarball snapshot/undo | hook.py, snapshot.py |
| Eval harness + labeled corpus + calibration | eval.py, tests/fixtures/eval_corpus.jsonl |
Calibration. Two harnesses, both run-it-yourself:
tests/fixtures/eval_corpus.jsonl, 58 cases spanning every recoverability category, git working-tree state, infra/config, rm -rf .git, a graph-indexed central module, the git/docker/pip/SQL classes, and the resolution layer — unset-var collapses, glob/env-var targets, sh -c payloads, npm pre-hooks, opaque wrappers, mass destruction of tracked source) — 58/58 exact severity, gate F1 1.00, pinned by tests/test_eval.py with headroom so changes can't silently regress.data_destruction) it catches 82.4% of injected attacks on realistic workspaces — on the fast hook path, no graph required, thanks to command resolution (env/glob binding + script transparency). Wrapper transparency also lifts code_tampering from ~0% to 50%. The per-category recall is deliberately uneven, and the table says so: blast-scope scores *destructive consequence* — filesystem/data loss plus git/docker/pip/SQL state. Network exfiltration and persistence are a different threat model, out of scope by design — not an unfinished corner. That's the boundary, drawn on purpose. See bench/.uv run python -m blast_scope.eval # in-repo corpus
python bench/saber_eval.py --tasks /dataset/data/tasks.jsonl # SABER
The fastest path for any MCP client is zero-install via uvx (no clone, no venv):
uvx blast-scope # runs the MCP server on stdio
Claude Code users — one line wires up both the MCP tools and the advisory hook:
/plugin marketplace add Atharva-Jayappa/blast-scope
/plugin install blast-scope
For development, or to pin a checkout:
git clone https://github.com/Atharva-Jayappa/blast-scope.git
cd blast-scope && uv sync --all-extras
Add to your MCP client config (e.g. Claude Code settings.json):
{
"mcpServers": { "blast-scope": { "command": "uvx", "args": ["blast-scope"], "type": "stdio" } } }
Tools exposed:
| Tool | Purpose |
|---|---|
assess_command(command, cwd?, project_root?) | Score a (possibly chained) command. Returns score, severity, rationale, evidence, recoverability, affected nodes, and a per-segment chain breakdown. |
index_project(project_root) | Force a dependency-graph rebuild (auto-built on first use otherwise). |
list_snapshots(project_root) | List undo snapshots, newest first. |
restore_snapshot(snapshot_id, project_root) | Undo a risky command by restoring its snapshot. |
Intercept Bash commands *before* they run — advisory, never blocking. Volume scales with stakes: silent on low/medium, advise on high, advise + snapshot on critical. The snapshot skips what's already recoverable (git-clean, regenerable) and warns rather than tars anything over a hard size cap, so the undo net stays fast and trustworthy.
The hooks also keep the dependency graph alive on their own — no MCP call needed: SessionStart cold-builds it in a detached background process, and every PreToolUse refreshes it incrementally before scoring (a ~20 ms stat sweep when nothing changed), so verdicts track the current tree even after a burst of agent edits. Add to .claude/settings.json:
{
"hooks": { "SessionStart": [ { "hooks": [{ "type": "command", "command": "python -m blast_scope.hook" }] } ], "PreToolUse": [ { "matcher": "Bash", "hooks": [{ "type": "command", "command": "python -m blast_scope.hook" }] } ] } }
Full details and the undo flow: docs/hook.md.
A filesystem command, scored against the dependency graph:
// assess_command("rm -rf ./config", project_root="/proj")
{ "score": 0.93, "severity": "critical", "recommendation": "block", "recoverability": "untracked", "rationale": "rm targets config. 8 direct importer(s), 14 total affected. not git-tracked. recursive deletion. CRITICAL risk.", "evidence": [ "8 importer(s), 14 affected node(s)", "high centrality (PageRank 0.91) — a hub other code routes through", "untracked — not in git history", "recursive — applies to every file underneath" ], "affected_nodes": [ /* ... */ ], "chain": [ /* per-segment breakdown */ ] }
A command class
Solo se muestra el principio; lee el resto en el repo