Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Catch spec drift before it catches you. Detect overlap, stale docs, and code drift.
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.
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Descargar el archivo .mcpb del creador
El enlace lleva al archivo del propio creador; no lo alojamos ni lo reempaquetamos. Abre el archivo y Claude Desktop lo instalará.
Ejecuta esto en tu terminal
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.
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 dusk-network, 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 (1.0.0-beta.12) llegó al registro hace 6 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas MCPB en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Python MCP
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.
Local-only Python MCP server for the Files.com API.
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.
Pituitary
Consistency governance for AI-native development.
Catch drifts before they catch you.
What It Catches · Quick Start · Agent · CI · Cheatsheet · Reference
*For developers and teams where human+AI continuously produce specs, docs, and decisions that should agree — and silently stop agreeing.*
Watch on asciinema for the interactive version.
Single binary. No Docker. No API keys required. One governance SQLite file plus one local Stroma snapshot.
The core shipped slice is local and CLI-first. The MCP server, CI wiring, and provider-backed semantic runtimes are optional wrappers around that same deterministic core.
You already know your docs drift. You fight it with LLM cleanup passes. The LLM says "all clean" — but it only covered what fit in the context window. The rest keeps rotting. Next PR introduces fresh contradictions on top of the ones that were never actually fixed. It's a treadmill that feels productive but never converges. Meanwhile the token costs pile up: false starts, misdirections, and wasted context directly caused by drifting issues, conflicting specs, and obsolete docs.
Pituitary replaces that treadmill with a structural guarantee: it indexes the entire corpus and checks all of it, every time. On a real repo with 11 specs and 29 docs, it found 90 deprecated-term violations across 22 artifacts and 7 semantic contradictions. The project direction was plagued by doc drifts, runtime contract contradictions, and deprecated terminology surfacing everywhere — Pituitary rescued it. Across multiple repos, it becomes the single point of truth where governance converges.
Overlapping decisions. A new spec covers ground an existing one already handles.
Stale docs. A spec changed, or a code diff implies docs likely went stale, but the CLAUDE.md, AGENTS.md, runbooks, and guides that reference it weren't updated.
Code that contradicts specs. Pipe your diff in before you merge:
git diff origin/main...HEAD | pituitary check-compliance --diff-file -
Terminology drift. The team adopted new language but old terms persist across your docs and specs.
Pituitary starts as a drift detector. As your intent corpus grows, it becomes the consistency governance layer:
Temporal governance. Point-in-time queries against the governance graph. When a spec is superseded, historical governance links are preserved but excluded from current queries. Use --at DATE with check-compliance, check-doc-drift, or analyze-impact. Timestamps are derived from index build/update time.
Confidence-weighted edges. Governance links carry trust tiers — extracted (declared in spec), inferred (AST symbol matching), or ambiguous. Use --min-confidence with check-compliance and check-doc-drift to trade precision for recall.
Deliberate deviation vs accidental drift. When code contradicts a spec, Pituitary checks for rationale comments (// WHY:, // HACK:, decision language). Deliberate deviations get a different remediation path than unintentional drift.
Governance changelog. index --update --show-delta reports what changed: specs added/removed, edges created/severed, governance posture shifts. The feedback loop CI needs.
Spec families. Community detection on the dependency graph discovers natural governance clusters. Coverage gaps between families are the highest-risk ungoverned areas.
Governance protocol for AI. The optional MCP wrapper teaches your AI assistant *when* to check governance — before modifying files, before committing, after accepting specs, when writing docs — not just how.
pituitary init --path . # discover, index, report
pituitary new --title "Rate limiting policy" --domain api # scaffold a draft spec pituitary check-doc-drift --scope all # find stale docs pituitary review-spec --path specs/X # full review of one spec pituitary status # index health and governance hotspots at a glance
| What you want to do | Command | |
|---|---|---|
| First run on a repo | pituitary init --path . | |
| Scaffold a new draft spec | pituitary new --title "Rate limiting policy" --domain api | |
| Find stale docs | pituitary check-doc-drift --scope all | |
| Find stale docs implicated by a diff | `git diff origin/main...HEAD \ | pituitary check-doc-drift --diff-file -` |
| Check a PR diff against specs | `git diff origin/main...HEAD \ | pituitary check-compliance --diff-file -` |
| Debug why a file is in or out of scope | pituitary explain-file PATH | |
| Full spec review | pituitary review-spec --path specs/X | |
| Auto-fix deterministic drift | pituitary fix --scope all --dry-run | |
| Search specs by hybrid relevance | pituitary search-specs --query "rate limiting" | |
| Trace impact of a spec change | pituitary analyze-impact --path specs/X | |
| Compare two specs | pituitary compare-specs --path specs/A --path specs/B | |
| Detect stale specs | pituitary check-spec-freshness --scope all | |
| Inspect command contracts | pituitary schema review-spec --format json |
All commands output JSON with --format json. Agents can set PITUITARY_FORMAT=json, and redirected stdout defaults to JSON automatically. review-spec also supports --format markdown and --format html for shareable reports with full evidence chains.
When file selection looks wrong, start with pituitary explain-file PATH. It is the fastest way to confirm which source matched a file, which selectors fired, and why a path was rejected before you debug drift or compliance output.
One pituitary.toml can also span multiple repository roots. Bind a source to a named repo root with repo = "...", and Pituitary carries that repo identity through search, drift, impact, status, and index output so cross-repo results stay unambiguous.
pituitary status now also flags governance hotspots so you can triage the corpus quickly: specs with unusually broad applies_to fan-out, artifacts that are only weakly governed through inferred or ambiguous links, and artifacts currently governed by multiple specs.
For terminology migrations, you can keep running ad hoc audits with --term / --canonical-term, or declare reusable [[terminology.policies]] in config and run pituitary check-terminology directly. Results now separate actionable current-state violations from tolerated historical uses, support terminology-only exclude_paths for historical containers such as CHANGELOG.md, and include replacement suggestions in both text and JSON output.
analyze-impact, check-doc-drift, and review-spec now emit section-level evidence chains in JSON: source refs on both sides of the match, a classification, a link_reason, and likely edit targets or suggested bullets. That gives agents enough structure to explain the next manual edit without scraping prose or auto-editing speculative changes.
For agent integrations, use pituitary schema --format json to inspect request/response contracts, and prefer --request-file PATH|- on analysis commands when shell escaping would be brittle. Results that include raw repo excerpts or evidence now carry result.content_trust metadata so callers can treat returned workspace text as untrusted input instead of executable instructions.
See the cheatsheet for every command, the full reference for configuration/runtime/spec details, the reusable multi-editor package at skills/pituitary-cli/README.md, and AGENTS.md for repo-native agent instructions.
macOS (Homebrew):
brew install dusk-network/tap/pituitary
Linux / macOS (binary): download from GitHub Releases, then:
tar xzf pituitary_*_*.tar.gz
sudo install pituitary /usr/local/bin/
Windows: download pituitary_ _windows_amd64.zip from GitHub Releases, extract pituitary.exe, and add its location to your PATH.
Build from source (contributors): see docs/development/prerequisites.md.
Your agent writes specs, reviews PRs, and proposes changes — but it doesn't know what's already been decided. Pituitary gives it that context. The governance protocol teaches it when to check, not just how.
{
"mcpServers": { "pituitary": { "command": "pituitary", "args": ["serve", "--config", ".pituitary/pituitary.toml"] } } }
Your agent gets 15 tools: search_specs, check_overlap, compare_specs, analyze_impact, check_doc_drift, review_spec, get_intent_outline, expand_intent_context, check_compliance, check_terminology, governed_by, compile_preview, fix_preview, status, and explain_file. For focused context, search first, inspect the returned record with get_intent_outline, then expand selected chunk IDs with expand_intent_context using the same snapshot_fingerprint.
cp -R skills/pituitary-cli ~/.claude/skills/pituitary-cli
Codex CLI and Gemini CLI get project policy from AGENTS.md / GEMINI.md automatically. For the full Pituitary analysis workflow, also install the skill package: cp -R skills/pituitary-cli ~/.codex/skills/pituitary-cli or ~/.gemini/skills/.
cp skills/pituitary-cli/platforms/cursor/.cursorrules .cursorrules # Cursor
cp skills/pituitary-cli/platforms/windsurf/.windsurfrules .windsurfrules # Windsurf cp skills/pituitary-cli/platforms/cline/.clinerules .clinerules # Cline
The repo's AGENTS.md is the canonical project policy. Tools that read AGENTS.md get Pituitary awareness automatically. Generated mirrors (CLAUDE.md, GEMINI.md) are compatibility outputs, not separate policy sources.
See skills/pituitary-cli/README.md for the full install guide, request templates, and security notes.
If you already use GitHub Actions, you can wrap the same local CLI workflow in the checked-in action and post review-spec output as a PR comment:
permissions:
contents: read pull-requests: read issues: write
steps:
Solo se muestra el principio; lee el resto en el repo