Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Manifest-driven MCP server scaffolder and runtime hub for tool integrations.
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": {
"factory": {
"command": "uvx",
"args": [
"jaimenbell-mcp-factory"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add factory -- uvx jaimenbell-mcp-factoryIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"factory": {
"command": "uvx",
"args": [
"jaimenbell-mcp-factory"
]
}
}
}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": {
"factory": {
"type": "stdio",
"command": "uvx",
"args": [
"jaimenbell-mcp-factory"
]
}
}
}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 8. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto jaimenbell 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 (0.1.3) kam vor 3 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Filesystem MCP
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.
Filesystem MCP server for AI assistants.
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.
*The test count is verifiable below (
python -m pytest tests/→ 348 passed, 8 skipped) and enforced in CI byscripts/check_readme_counts.py, which fails the build if this README's counts drift from the live suite.*
From PyPI (registry users):
pip install jaimenbell-mcp-factory
mcp-factory-hub --serve
From a git checkout (contributors): see the python hub_server.py ... examples throughout this README — hub_server.py at the repo root is a backward-compat wrapper around the same mcp_factory.cli module the console script runs, so behavior is identical either way.
The manifest-driven engine behind the MCP Integration Sprint. Write one mcp.yaml for a bot repo and the factory generates the server stub and the ~/.claude.json entry; run the hub and it serves every bot's tools through a single MCP endpoint.
The SDK wrapper is the easy part. What makes an MCP server safe to put in front of a real internal tool — scoped auth/env, fail-soft error handling, validated manifests, a collision-safe registry, and a real test suite — is the engineering this engine is built around. That same production layer is hand-built per engagement; the factory scaffolds it, it doesn't fake it.
This repo is public so you can verify the discipline instead of taking my word for it. Every claim below maps to a file you can open:
| Claim | Where it lives | What to look for |
|---|---|---|
| Validated, env-scoped manifests | mcp_factory/manifest.py | strict from_dict validation (raises on missing/invalid fields); the env_required / env model that scopes which secrets a server may see |
| Fail-soft subprocess proxying | mcp_factory/runtime/subprocess_adapter.py | typed SubprocessError, lazy start, JSON-RPC error surfacing, timeout/OSError-guarded teardown + atexit cleanup — a dead bot returns a clean error, it doesn't crash the hub |
| Collision-safe, manifest-driven registry | mcp_factory/runtime/registry.py · registry.json | CollisionError on duplicate . names; the registry is built from manifests, not hand-maintained |
| Tested on a clean checkout | tests/ | 348 passed, 8 skipped, 0 failed (Python 3.12); the 8 skips are real integration tests or lint checks that no-op when the thing they need is absent |
Honesty rails:
348is the real, reproducible count on a clean checkout — the same number the public CI run produces and gates on. mcp-factory generates the *scaffold* and runs the hub — it does not "generate the production server" or carry any client/CI claims. The hardened production layer (per-tool auth boundaries, the full failure set, two-axis version-pinning) is built per engagement on top of this engine. That applies to both Python scaffold styles below — see "Two Python styles" for exactly what the fastmcp variant does and doesn't add on top of that baseline.
# Reference an existing MCP server (no code generated — just the config entry)
python hub_server.py --manifest examples/fleet_health.yaml
python hub_server.py --manifest my_bot/mcp.yaml --output-dir my_bot/
python hub_server.py --manifest my_bot/mcp.yaml --dry-run
python hub_server.py --manifest examples/fleet_health.yaml --verify ~/.claude.json
Output always goes to ~/.claude.json.factory-test by default — never to the live ~/.claude.json. Copy entries manually after review.
# Dry-run diff: show what would change in ~/.claude.json
python hub_server.py --scan C:\path\to\projects
python hub_server.py --scan C:\path\to\projects --apply
python hub_server.py --scan C:\path\to\projects --apply --force
--scan discovers all projects/*/mcp.yaml files, validates each, and diffs them against the current ~/.claude.json. Default root is C:\path\to\projects. With --apply, a timestamped backup is created at ~/.claude.json.scan-backup- before writing.
Skip logic: manifests whose name already exists in ~/.claude.json are skipped unless --force is passed. This prevents accidentally overwriting manually-crafted entries.
# Run the hub as a live MCP server (stdio transport)
python hub_server.py --serve
python hub_server.py --serve \ --scan-root C:\path\to\projects \ --scan-root C:\path\to\Claude
python hub_server.py --register \ --scan-root C:\path\to\projects \ --scan-root C:\path\to\Claude
The hub scans all mcp.yaml manifests under each --scan-root at startup, then exposes every bot's tools under the . namespace (e.g., fleet-health.fleet_status, my-bot.run_scan). Tools are proxied to per-bot subprocess MCP servers with lazy startup.
Hub meta-tool: _hub.list_bots returns the registered bots and their subprocess status.
Hub is pre-registered in ~/.claude.json as mcp-factory-hub (see scripts/register_hub.py).
Factory generates Node.js stubs when runtime.type: node is set in mcp.yaml:
runtime:
type: node command: "node" output: "path/to/server.js"
Generated stubs use @modelcontextprotocol/sdk with stdio transport and zod for argument validation. See examples/node_example.yaml for a working demo.
For runtime.type: python, the factory can scaffold either of two styles from the exact same manifest:
runtime:
type: python command: "python" style: raw # default — official mcp SDK, hand-rolled list_tools/call_tool
Both styles read the same tools: / env_required: fields and produce a server that speaks the same stdio JSON-RPC wire protocol — the runtime hub's SubprocessAdapter proxies either one without any adapter changes (see tests/test_fastmcp_template.py::TestFastmcpServeSmoke for a live generate-and-call test).
style: raw (python_server.py.j2) | style: fastmcp (python_fastmcp.j2) | |
|---|---|---|
| SDK | official mcp package, mcp.server.Server | fastmcp (pinned exact fastmcp==3.4.2 — 4.0.0b1 is a beta that breaks sampling/roots, do not float) |
| Tool registration | manual @server.list_tools() / @server.call_tool() dispatch | one @mcp.tool(...)-decorated function per tool |
| Arg schema | hand-built JSON Schema dict per arg | Annotated[type, Field(description=...)] on real Python parameters — FastMCP derives the JSON Schema, including required/optional, from the signature |
| Tool body | # TODO: implement stub | same stub, wrapped in try/except Exception — a runtime error in a filled-in implementation returns a structured {"status": "error", ...} instead of crashing the process |
env_required | not enforced at scaffold level | rendered into a _check_required_env() startup check that warns to stderr if a declared var is missing — a presence check, not credential validation |
Gaps, stated honestly: neither style implements per-tool authorization, rate limiting, or the "full failure set" the hub-level subprocess_adapter.py gives you for free (typed errors, lazy start, atexit cleanup) — that's still a per-engagement build on top of either scaffold. The fastmcp template's fail-soft wrapper and env-presence check are new, real code (read mcp_factory/templates/python_fastmcp.j2), not a marketing claim about auth — they were added because FastMCP's decorator model made them cheap to include cleanly; they have not (yet) been backported to the raw template, which is why the two styles differ slightly in what ships out of the box. If your engagement needs FastMCP-specific features beyond this (resources, prompts, HTTP/SSE transport, middleware-based auth), the generated file is a normal FastMCP app — extend it directly.
See examples/fastmcp_example.yaml for a working demo manifest.
name: my-bot # REQUIRED — unique MCP server name (key in claude.json)
description: > # REQUIRED — shown in Claude's tool descriptions What this bot does and when to use it.
runtime: # REQUIRED type: python # python | node | binary command: "C:\\Python314\\python.exe" # full path to interpreter script: "path/to/server.py" # existing server (skips scaffold generation) output: "path/to/out.py" # where to write generated scaffold (omit = auto) style: raw # python only: raw (default) | fastmcp — see "Two Python styles"
tools: # REQUIRED — list of MCP tools to expose
env_required: # env var names that must be set at runtime
env: # static env vars injected into claude.json entry MY_API_KEY: "" # leave value empty — fill in ~/.claude.json manually
tags: [trading, health] # for documentation / future routing priority: high # high | medium | low
runtime.script + existing file → factory references it, skips scaffoldruntime.script + missing file → validation error (use runtime.output for new scaffolds)runtime.output → explicit path for generated stub (absolute recommended)script nor output → error at config-write steptitle and annotationsBoth are optional and both are worth declaring.
title is the human display name, which lets name stay a programmatic identifier. Display precedence is title → annotations.title → name; the factory exposes only the top-level title so one manifest cannot declare two competing display names.
annotations matters more than it looks. The four hints have pessimistic defaults — destructiveHint and openWorldHint both default to true, readOnlyHint to false —
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