dsh-crew

mcp
Guvenlik Denetimi
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  • License — License: MIT
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  • Active repo — Last push 0 days ago
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  • network request — Outbound network request in lib/client.js
  • network request — Outbound network request in src/client/index.tsx
  • process.env — Environment variable access in src/hub-client.mjs
  • network request — Outbound network request in src/hub-client.mjs
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Bu listing icin henuz AI raporu yok.

SUMMARY

DeepSeek Harness (DSH) plugin: dispatch work to DSH agents from Claude Code / Codex — native subagent progress, in-host worker sessions with per-tier presets, and a multimodal bridge that lends the text-only harness vision and image generation.

README.md

DSH Crew

DSH Crew

A DeepSeek Harness plugin: dispatch work to DSH agents from Claude Code / Codex, without giving up the host's native subagent UI.
Native Progress UI • Tier Policy & Escalation • In-Host DSH Sessions • Vision & Image Generation • One-Click Install

npm: @zseven-w/dsh-crew · Current plugin release: 0.1.0-rc.1 · Tested with DSH 0.1.0-rc.6

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License


DSH Crew — settings page

The DSH Crew settings page — host integrations, dispatch policy, execution and the multimodal bridge

Why DSH Crew

DSH Crew is a plugin for DeepSeek Harness (DSH) — an open-source agent harness. It makes DSH agents dispatchable from Claude Code and Codex: the orchestrator keeps its own model, the work runs on a real DSH agent with that harness's tools, sandbox, presets and session history, and the host still shows it as a native subagent with live progress.

What runs the work is a DSH agent, not a bare model call. Tiers (flash / pro) select how much capability that agent gets from the harness's configured roster — DeepSeek V4 Flash and V4 Pro today — so a change of model in DSH needs no change here.

🧵 Native Progress UI

Workers appear as regular subagents in Claude Code / Codex — dispatch count, running step, tool calls and token usage all show up in the host's own task panel, plus a claude-hud statusline segment: ⚙dsh 1▶pro 2m14s 21.7k/606 ✓3.

🎚️ Tier Policy and Escalation

flash for mechanical work, pro for reasoning, effort from off to max. tier_policy can clamp every dispatch to one tier at the tool layer, and escalate_on_failure retries a failed flash run once on pro — based on evidence, not on guessing difficulty up front.

🏛️ In-Host DSH Sessions

With the bundle installed in a DSH profile, each worker is a first-class DSH session: visible in the Web UI, grouped by working directory, mounted with the Agent preset you choose per tier. Without DSH running, dispatch falls back to a standalone DSH runtime, so CI and headless environments still work.

👁️ Vision and Image Generation

DSH's models are text-only. describe_image and generate_image borrow the eyes and brush of the CLIs you already have — Claude, Codex, Grok, Antigravity — or of any OpenAI-compatible API you configure. Pasted images stay visible in the conversation and reach the model as text.

🔌 Custom Providers

Bring your own endpoint (Base URL + API key + models) or a local command template. Each provider has a connectivity test that checks reachability and auth, then makes one real vision call so you find out now, not mid-task.

📦 One-Click Install

The settings page installs and updates the Claude Code plugin and the Codex role files for you — marketplace registration, permission allowlist, HUD wiring, absolute paths rendered for this machine — and restores them just as easily. Every settings file is backed up first.

How it works

Claude Code / Codex (orchestrator, keeps its own model)
  └─ ds-flash / ds-pro  ← native subagent shell (progress shows in the host's task UI)
       └─ MCP: dsh_run_worker(tier, effort, cwd)
            ├─ hub reachable → session inside DSH (visible in the Web UI, grouped by cwd)
            └─ otherwise     → dsh-jsonrpc-agent runtime (worker.cordis.yml)
                 └─ DeepSeek V4 Flash / Pro (DSH SDK, event stream → progress and token stats)

One run, two views

Dispatch fans out. Below, eighteen workers translate this README in parallel: the host counts them as its own subagents, while the harness runs them as real sessions.

Claude Code

Claude Code sees dsh-crew workers as native subagents, with a statusline segment tracking running tiers, elapsed time and tokens.

DSH Crew

The DSH Crew panel sees the same run from the harness side: which host dispatched each job, its tier and effort, live progress and token usage.

Install

Install into a DSH profile from npm:

dsh plugin --profile web add @zseven-w/dsh-crew@latest
dsh web

Or, for local development straight from the source tree:

dsh plugin --profile web add link:/path/to/dsh-crew
dsh web

The link: protocol symlinks the profile dependency to this repository, so rebuilds are visible immediately.

Configure DeepSeek credentials (standalone only)

In hub mode — the installation above — workers run inside the DSH instance and use the DeepSeek credentials it is already configured with. Nothing else to set up.

Only the standalone fallback needs a key of its own: dispatching from Claude Code / Codex with no DSH instance running launches a worker runtime as a separate process. Obtain an API key from platform.deepseek.com and write it to ~/.config/dsh-crew/.env:

DEEPSEEK_API_KEY=sk-...

Verify

node scripts/smoke.mjs

The smoke test exercises the standalone path, so it needs the key above. Within about ten seconds you should see smoke test passed — configuration OK. On failure the reason is printed; usually the key is missing or invalid.

Then open Settings → DSH Crew and install the Claude Code / Codex integrations with one click.

Background and terminology

  • DSH (DeepSeek Harness): DeepSeek's open-source agent harness, a code agent in Web UI form, similar to Claude Code but driving DeepSeek models.
  • MCP (Model Context Protocol): Anthropic's AI tool integration protocol, enables LLMs to safely call external tools and data sources.
  • Cordis bundle: DSH's plugin format; this project can run standalone as an MCP service or install into DSH Web as hub mode.
  • tier: capability tier — which slot of DSH's configured model roster a worker gets. flash is fast and cheap (simple tasks), pro reasons harder (complex problems). Today they map to DeepSeek V4 Flash and V4 Pro; swap models in DSH and nothing changes here.
  • worker: the DSH agent doing the work — a full session with its own tools, sandbox and preset, not a bare model call.
  • effort: reasoning strength, off = no reasoning, high = high reasoning investment, max = maximum reasoning investment.

Claude Code

Installation

One-click installation (choose one):

  • DSH settings page (when hub mode is installed): Settings → DSH Crew → "Install to Claude Code"
  • Command line: node src/install/cli.mjs all

Both do the same thing: register local marketplace (parent directory dsh-plugins/ as marketplace root) + claude plugin install + MCP tool permission allowlist + claude-hud worker status segment config (auto-backup settings.json before changes, idempotent). Restart the session after installation for changes to take effect.

Usage

  • Directly in conversation, say "dispatch X to ds-flash" or "dispatch X to ds-pro", and subagent executes the task
  • Dispatch count and real-time progress shown in Claude Code task UI
  • HUD status line segment: ⚙dsh 1▶pro 2m14s 21.7k/606 ✓3 (current tier / elapsed time / token usage / completion count)
    • For local development, statusline/statusline.sh or statusline/worker-segment.sh can be independently integrated
  • Long-running tasks: CC has timeout limits on MCP calls (MCP_TOOL_TIMEOUT adjustable), long tasks can have orchestrator use dsh_spawn_worker + dsh_worker_result(wait_seconds) polling
  • Local development and debugging: claude --plugin-dir /path/to/dsh-crew to temporarily load

Session commands

These override the global defaults for the current session only, and are enforced at the tool layer rather than by prompting:

Command What it does
/dsh-crew:config Show or set this session's defaults: tier=flash|pro, effort=off|high|max, mode=auto|hub|standalone, timeout=<seconds>, policy=auto|flash-only|pro-only, escalate=true|false, reset
/dsh-crew:on · /dsh-crew:off Turn dispatch for this session on or off (off is a hard switch: the tool refuses)
/dsh-crew:status Live status of worker jobs: tier, progress, tokens, current tool

Codex

Installation

Recommended to use the installer (auto-renders paths for this machine, copies /dsh-config, /dsh-status commands):

node src/install/cli.mjs codex

Or manually copy (requires manual path modification after copying):

cp codex/agents/*.toml ~/.codex/agents/    # global or project-level .codex/agents/

Role files come pre-configured with:

  • MCP server mounting configuration
  • default_tools_approval_mode = "approve" (required, otherwise tool calls are auto-cancelled in exec mode)
  • tool_timeout_sec = 3600

Note: When manually copying, absolute paths in the args field must be updated to match actual installation location; the installer handles this automatically.

Usage

  • In interactive TUI, select "spawn ds-pro to ..." to dispatch tasks; Active/Done panels show progress
  • codex exec mode can also directly call dsh_run_worker

Session commands

The same two prompts are installed for Codex:

Command What it does
/dsh-config Show or set this session's defaults: tier=flash|pro, effort=off|high|max, mode=auto|hub|standalone, timeout=<seconds>, policy=auto|flash-only|pro-only, escalate=true|false, reset
/dsh-status Live status of worker jobs: tier, progress, tokens, current tool

MCP tools

Tool Description
dsh_run_worker Synchronous task dispatch (tier: flash/pro, effort: off/high/max, cwd), waits for result
dsh_spawn_worker Asynchronous task dispatch, returns job id (for parallel fan-out)
dsh_worker_status Query real-time progress of all jobs (turn/step/current tool/token)
dsh_worker_result Fetch result, can specify wait_seconds to wait
dsh_worker_cancel Cancel specified job, terminate its runtime process

Progress is simultaneously mirrored to ~/.config/dsh-crew/status.d/ (one shard file per writer, can be read by statusline / external monitoring).

Multimodal: vision and image generation

DeepSeek is a text-only model and does not support image input or generation. This plugin sources these capabilities externally through MCP tools:

Tool Description
describe_image Answer questions by viewing images (screenshots, designs, charts, etc.), results cached by provider + model + image + question
generate_image Generate image from text description, save to specified absolute path; output is flat bitmap (requires OpenPencil for layer editing)

Session image pasting: In DSH, switch model to DeepSeek (vision) ◉ to directly paste images. Images remain in session and display normally; the plugin appends transcribed text after them and strips images before sending—you see the image, the model reads the text.

Configuration

In DSH settings page → DSH Crew → Multimodal (or directly edit ~/.config/dsh-crew/config.json):

Vision provider (image viewing):

  • claude-code (default, uses haiku, inexpensive)
  • codex (uses GPT, can specify specific model)
  • grok (uses Grok)
  • agy (Antigravity)
  • custom (OpenAI-compatible API or local command)
  • off (disabled)

Image generation provider (image generation):

  • codex ($imagegen, gpt-image-2)
  • agy (Nano Banana)
  • grok (Imagine)
  • custom (OpenAI-compatible API or local command)
  • off (disabled)

Custom provider

Two integration methods:

API: Any OpenAI-compatible endpoint

  • Fill Base URL, API Key, model list
  • Vision uses /chat/completions with inline base64 images
  • Image generation uses /images/generations
  • Must specify "image generation model" to have generation capability, otherwise provider only appears in vision selection

CLI: Local command template, placeholders substituted with safe references

  • Vision: {image} {question} {model} → stdout as answer
  • Image generation: {prompt} {output} {size} → command must write file to {output}
  • Fill at least one command; whichever is filled determines capability

Connectivity test: Each custom provider has a test button

  • API: Check endpoint reachability, auth, send real vision request to verify
  • CLI: Check executable file, run real command to verify
  • Image generation: Validate config only, no actual image output

Borrowed subscription CLIs (claude / codex / grok / agy) require you to be logged in locally; the plugin won't bypass their permissions for you.

Hub mode

This package is also a valid DSH bundle (dsh.bundle + cordis.patch.yml). After installing into DSH Web profile with dsh plugin add dsh-crew:

  • Worker sessions become first-class citizens: run as first-class sessions in DSH host (agents.create + per-session model/effort waterfall + default preset), appear in Web UI session list, can be opened anytime to view complete execution
  • Organize by working directory: manage worker sessions by cwd in Web UI
  • Loopback API:
    • POST/GET /_dsh/dsh-crew/jobs: spawn tasks, list, long-poll results, cancel
    • GET /_dsh/dsh-crew/ping: health check (MCP shim uses this to detect if hub is running)
    • POST /_dsh/dsh-crew/install: one-click install Claude Code / Codex integration (backend of src/install/)
  • Auto-detection: CC/Codex's MCP shim auto-detects hub (DSH_CREW_HUB env var, default http://127.0.0.1:3080)
    • DSH Web running → jobs enter hub mode (mode: "hub")
    • Not running → fall back to standalone runtime

Solution selection and limitations

Regular subscribers → shell subagent approach (recommended)

  • Current state: Claude Code subagent shell uses haiku as intermediary; each dispatch adds hundreds to thousands of tokens
  • Trade-off: Use small amount of Anthropic token in exchange for native task UI, real-time progress display, no extra configuration
  • Recommendation: If you already subscribe to Claude Pro or use Claude Code, use this approach—convenient and transparent

Pay-as-you-go / CI environments → direct router approach

  • Current state: Claude Code subagent frontmatter doesn't support direct third-party model connection; this repo's router experiment in scratchpad requires API-key credentials for Claude Code, but subscription OAuth is blocked upstream by Anthropic with 403
  • Recommendation:
    • If using API-key credentials (not OAuth) and want to save Anthropic tokens, can run local router for direct DeepSeek connection
    • CI environments typically also use API keys; this approach is more economical (all DeepSeek tokens)
    • Requires self-testing of router integration (not officially supported)

Running DSH Web → hub mode auto-enabled

  • Current state: If dsh plugin add dsh-crew installed into DSH Web profile, jobs run as first-class sessions in host, appear in Web UI session list
  • Recommendation: During local development iteration, recommend enabling hub mode; worker progress can be fully observed in Web UI; for cross-machine collaboration or environments without Web UI, use Claude Code / Codex shell approach

Known items

  • Codex role can theoretically try model_provider pointing directly to DeepSeek (unverified); this bridge doesn't depend on it
  • Image generation output is flat bitmap; layer editing requires OpenPencil
  • Runtime dependencies: Only @modelcontextprotocol/sdk and zod; @deepseek-ai/* are peerDependencies (provided by DSH host)
  • Codex must configure: default_tools_approval_mode = "approve", otherwise tool calls are auto-cancelled

Develop

pnpm install
node_modules/.bin/tsdown src/client/index.tsx --format cjs --platform browser \
  --target es2022 --tsconfig tsconfig.client.json --out-dir .client-build --clean
node scripts/build-client.mjs   # wraps the bundle for the DSH module loader
node scripts/smoke.mjs          # dispatches one real flash task end to end

Runtime dependencies are only @modelcontextprotocol/sdk and zod; every @deepseek-ai/* package is a peer dependency provided by the DSH host, which keeps the plugin inside the host's single module realm.

Ecosystem

  • DSH Noema — long-term memory for DSH
  • DSH OpenPencil — inspect and edit .op design documents inside a conversation

License

MIT

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