Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Report agent jobs to the TaskHub Windows tray app: progress, notifications, buttons (app required).
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
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Download the maker’s .mcpb file
The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.
Run this in your terminal
Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account FelixMUrphy, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (3.1.0) reached the registry 3 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Apify MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
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One place to watch and control everything that runs in the background on your Windows PC — training runs, simulations, renders, builds, backups, and the scripts your AI agents (Claude, Codex, ChatGPT) start for you.
Any process reports progress over a tiny local HTTP API and gets a tray icon, Windows notifications and a pop-up panel with live charts, gauges and its own buttons (pause, change a parameter, save a snapshot, kill). No cloud, no account, loopback only.
Demo data, recorded by a script — a render reports progress and a chart, asks "upload to the NAS?" in a notification and in Telegram, and goes on when the answer is tapped on the phone.
⬇ Download the latest setup.exe · What's new · API reference · Privacy · ❤ Sponsor
AI agent reading this? Claude Code / Codex: use the TaskHub MCP tools (
task_start,notify, …). If you don't
see them, don't use
curl- ask the user to enable *TaskHub tools (MCP)* (panel → ⚙ *Settings* → *AI agents*) and to start a new session. Details: API.md → AI agents.
&, |…)./tasks, /mute (optionally only when you are away from the PC) — see Telegram.taskhub mcp), a native taskhub CLI on PATH, a stdlib-only Python client, plain HTTP for everything else; taskhub api prints the docs an agent needs.TaskHub- -setup.exe → Install (choose a folder, autostart, PATH and the Claude Code / Codex options). From 2.9 the setup window stays open with the progress and ends with *Open TaskHub*; uninstalling works the same way (with an optional *Also delete my data*).taskhub notify "Render" "finished in 42 min"
taskhub run --name "Build" -- cmake --build build -j 16 # wraps any command, parses % from its output taskhub run --name "Shot 12" -- blender -b shot12.blend -s 1 -e 240 -a # 2.9.2: frame, samples, overall %, s/frame
*From version 2.9.2:* taskhub run knows Blender's background-render output by itself (no add-on in Blender): the frame and its samples, overall progress when the frame range is known (-s/-e or -f), a seconds-per-frame chart and the last saved file, render memory. Blender exits with 0 even when a render fails, so its Error: lines mark the task failed (and taskhub run exits with 1; not the memory-leak note Blender prints at exit). Video output (FFmpeg) and stereo views saved as separate files count by frame (2.9.3). *Stop after this frame* (panel / notification) ends Blender once the frame is saved and the next one begins; after such a stop or a crash the task says where to resume and taskhub run prints the same command with -s set to the next frame. --preset none turns this off.
from taskhub_client import Task, W, C # stdlib only; installed next to taskhub.exe
with Task("Train", total=100, unit="epochs", source="codex", widgets=[W.chart("loss", "Loss", series=["train", "val"]), W.gauge("vram", "VRAM", max=24, unit="GB")], controls=[C.signal("lr", "Set LR", input=C.number(default=1e-3))], pausable=True) as t: t.on("lr", lambda v: set_lr(v)) for e in range(100): t.wait_if_paused() if t.stop_requested: break t.progress(e + 1, status=f"epoch {e+1}", widgets={"loss": {"train": tl, "val": vl}, "vram": mem})
curl -s -X POST localhost:47800/api/notify -H "X-TaskHub: 1" -d '{"title":"Done","message":"backup ok"}'
With AI agents — Claude Code and Codex: enable *TaskHub tools (MCP)* (next section), nothing else to do. Other agents (ChatGPT, scripts, any tool with a shell) — add one line to AGENTS.md / custom instructions:
For any job longer than a minute, report it to TaskHub (
taskhub apiprints the docs; wrap commands with
taskhub run --name ... --).
The setup dialog (and later Settings → *AI agents*) has independent options per agent. From 3.1, if an agent is used on your PC and you haven't chosen yet, the panel shows a card until you choose, one notification says so, and nothing is written until you press *Connect*:
| Option | What you get | Where TaskHub writes |
|---|---|---|
| Notifications (hooks) | a toast when the agent finishes a response or needs your permission | Claude Code: ~/.claude/settings.json · Codex: ~/.codex/hooks.json |
| Plan limits (from 3.1, off until you turn it on in Settings → AI agents, for each agent) | how much of the 5-hour and weekly limits is used, in the panel, yellow with a warning from 75%, red with a warning from 90% | Claude Code: ~/.claude/settings.json (statusLine) · Codex: nothing, TaskHub asks it directly |
| TaskHub tools (MCP) | the agent gets tools notify, task_start/update/finish, task_commands, task_wait (from 2.9.2), task_list and shows its long jobs in the panel by itself | Claude Code: ~/.claude.json · Codex: ~/.codex/config.toml |
TaskHub adds — and on uninstall removes (Store edition: see below) — only its own entries and keeps everything else (backup of the original: *.taskhub.bak). What to do in the agent afterwards:
/mcp should list taskhub as connected. Cloud sessions run on Anthropic's servers and can't reach TaskHub on your PC.esc to interrupt. Details: API.md.Only the beginning is shown; read the rest in the repo