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Ops Mcp — DSH Plugin for DeepSeek Harness
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dsh-ops-mcp

Ops Mcp

Operate DeepSeek Harness (dsh) over MCP: expose dsh sessions, task execution, and workspace management as an MCP server for any MCP client.

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add github:Leawind/dsh-ops-mcp#ec87162405047cba2653ec6ad36d191fb4891c4d
READMECompatibilityVersions

Compatibility and provenance

Ops Mcp is published as dsh-ops-mcp and currently resolves to version 0.5.0. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
web
Release source
github
Registry updated
9/22/2026

Versions

0.5.0stable
9/22/2026
0.4.0stable
9/22/2026
0.2.0stable
9/22/2026

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README

dsh-ops-mcp

Operate DeepSeek Harness (dsh) over MCP: run an MCP server inside the dsh process and expose session execution, task queues, and workspace management to any MCP client.

📖 English (this page) · 中文

What it does

dsh ships a complete agent runtime — model routing, tool sandbox, presets, persistent sessions — but it is a Cordis application that external programs cannot call directly. dsh-ops-mcp turns it inside out: the plugin starts an MCP server (StreamableHTTP) inside the dsh process and bridges the live harness through ctx.agents / ctx.agentPresets / ctx.tools.

Your MCP client is the commander; dsh is the executor. Works with Claude Code, Codex CLI, Cursor, another dsh instance (via the official dsh-mcp-client), or any automation script.

MCP client (Claude Code / Codex / another dsh / …)
   │  agent_run / task_inbox / task_result / model_list / select_model (HTTP + Bearer)
   ▼
dsh-ops-mcp (MCP server, 127.0.0.1:8090)
   │  ctx.agents.create → mount preset
   ▼
dsh agent — full toolset: bash, fs, todo, web…

Tools

ToolPurpose
echoconnectivity check
dsh_list_toolslist the host-global tool registry (name + description; model tools are preset-scoped, usually empty)
model_listlist currently routable providers, model ids, reasoning efforts, and the default selection (look here before picking a model)
agent_runrun a task synchronously, structured result; sessionId continues a session; provider/model/reasoningEffort pick this run's model; detail controls result size
task_inboxpush a structured task (task + context + cwd + model) into the async queue, returns taskId
task_resultfetch a queued task's result; detail=status is a lightweight poll that never re-injects the payload
select_modelswitch the model of an existing session (official sessionController.selectModel path)
attach_sessionattach a session to the workspace of its cwd
rename_sessionrename an existing session

Model selection

Priority: per-call arguments > plugin config (provider+model) > host default selection (ctx.agentDefaultModel.currentSelection(), the same source the Web UI uses when creating a session). Supplying only one half completes it from the lower-priority source; if the pair still cannot be resolved the call fails loudly instead of running with an empty model (an empty model leaves the persona's {{model}} variable unset and fails the whole turn at assembly time).

reasoningEffort follows the model's source: call argument > plugin config > the host default selection's own effort. But when the caller or the plugin config pins provider+model explicitly, the host's effort (chosen for some other model) is not inherited — the host rejects unsupported explicit efforts instead of clamping or aliasing, so inheriting one would break a deployment that used to work.

Three ways to change models:

GoalHow
Run this one task on another modelpass provider+model (plus optional reasoningEffort) to agent_run / task_inbox
Switch models mid-conversation, keeping historyselect_model (official sessionController.selectModel: validated, writes a durable notice, takes effect on the next step; history is preserved)
Pin one model for the whole deploymentset provider+model in the plugin config and allowModelOverride: false to refuse caller overrides

Two source semantics worth knowing:

  • The resident session pool is keyed by cwd + model triple. Task 1 on model A and task 2 on model B in the same directory are two separate sessions (no shared context), so which model a session uses is always predictable; to switch models inside one session, use select_model.
  • Results now carry model: {provider, model, reasoningEffort?} so the caller never has to guess who answered.

model_list's source names the catalog's origin: sessionController = the official view (same data source as the Web UI's model selector; includes default, routableProviders, per-provider load failures, and reasoning efforts); llm = fallback (llm.listProviders() + per-provider listModels(), for deployments without sessionController, e.g. headless, and without reasoning metadata). It also reports the plugin's own model config and allowModelOverride, so a caller can see at a glance whether it may choose.

Result detail levels (token budget) — the whole point of this plugin is saving the caller's (operator's) context: execution details stay inside dsh, and read-back is projected by detail:

  • summary (default, a few hundred tokens): the changes/verification/leftovers three-line summary + the answer tail (the summary JSON sits at the end) + tool-name list + error
  • normal (~2k tokens): the above + truncated tool-call arguments and results
  • full (up to tens of thousands of tokens, for debugging): the full text
  • task_result also has a status level: polling returns only {taskId, status, error?} — fetch the summary once after completion instead of re-injecting the payload on every poll

When continuing the same sessionId, the executor already remembers prior turns — send only the delta in context.

Every result is structured: sessionId / model / assistantText / toolCalls / toolResults / changes / verification / leftovers — ready to be persisted by the caller.

Sessions are reused per cwd + model (LRU, default 8) to avoid reloading project context on every call.

Install & run

The plugin must be installed into a dsh profile directory (the loader resolves plugin names from there; --patch alone from a repo checkout will not find the local package — see finding 1 in the E2E report):

git clone https://github.com/Leawind/dsh-ops-mcp.git
cd dsh-ops-mcp
npm install && npm run build
npm pack                                        # produces dsh-ops-mcp-<ver>.tgz

# install into the profile (Windows note: use the tarball; pnpm mangles file:D:/... specifiers)
pnpm -C ~/.dsh/profiles/<profile> add -w <path-to-tarball>

export DEEPSEEK_API_KEY=...                     # model credentials (or use what ~/.dsh already stores)
dsh --profile <profile> --patch ./cordis.yml --no-open --port 3081

The MCP server listens on 127.0.0.1:8090 (StreamableHTTP). Point any MCP client at http://127.0.0.1:8090/mcp.

Client configuration

Generic (any streamable-http capable MCP client):

{
  "mcpServers": {
    "dsh": {
      "url": "http://127.0.0.1:8090/mcp",
      "headers": { "Authorization": "Bearer <your-secret-token>" }
    }
  }
}

Let another dsh operate this one (add to the peer profile's cordis.patch.yml, using the official dsh-mcp-client):

- id: mcp-dsh-ops
  name: '@deepseek-ai/dsh-mcp-client'
  config:
    serverName: dsh
    transport: streamable-http
    url: http://127.0.0.1:8090/mcp
    headers:
      Authorization: 'Bearer <your-secret-token>'

cordis.yml (patch format)

- insert:
    - id: dsh-ops-mcp
      name: 'dsh-ops-mcp'
      config:
        http: true
        port: 8090
        host: 127.0.0.1        # localhost only by default; add auth before exposing
        # authToken: 'your-secret-token'   # Bearer token auth (constant-time compare)
        # workspaceRoots: ['/workspace']   # cwd whitelist (separator/case-safe cross-platform)
        # allowedHosts: ['my-box.lan']     # extra allowed Host header values (DNS-rebinding guard)
        # preset: 'standard'               # agent preset to mount
        # model: ''                        # empty = follow dsh user/default settings
        # provider: ''                     # pair with model; empty = follow host default
        # reasoningEffort: ''              # default reasoning effort (empty = adapter default)
        # allowModelOverride: true         # false = pin the model, refuse caller overrides
FieldDefaultMeaning
host / port127.0.0.1 / 8090MCP server bind address; a listen failure (port in use, …) fails plugin startup loudly
authToken—Bearer token; enforced on every request when set (constant-time compare)
workspaceRoots—cwd whitelist; agents may only work inside the listed directories (subdirs included)
allowedHosts—extra allowed Host-header values; the bind host and loopback aliases are always allowed, everything else gets 403
provider / modelfollow host user settings (agentDefaultModel)spawned-agent model selection; configure as a pair — a partial setting is completed from the host default
reasoningEffortadapter defaultdefault reasoning effort (adapter-defined id, see reasoningEfforts in model_list)
allowModelOverridetruewhether callers (agent_run/task_inbox/select_model) may override the model; false pins it and refuses overrides explicitly
presetstandardagent preset to mount
defaultDetailsummarydefault detail level for agent_run/task_result (overridable per call via detail)
reattachOrphansfalsebulk-attach ungrouped sessions to workspaces at startup (writes user data; the attach_session tool remains available anytime)
maxQueue / taskTtlMs / maxAgents100 / 10 min / 8queue capacity, result TTL, session-pool LRU limit

Every result is structured: sessionId / model / changes / verification / leftovers / error / toolCallCount … (projected by detail level); error carries non-normal turn endings (model failure / cancel / blocked), so a silent empty "success" can no longer happen.

Zero host copies

The plugin has zero runtime dependencies on @deepseek-ai/*: every dsh capability is reached through injected host services (ctx.agents / ctx.tools / ctx.agentPresets …), types only augment the compiler via import type (erased at build), and @deepseek-ai/* packages are devDependencies. A plugin therefore can never drag a mismatched copy of a host package into the process — the root cause behind the upstream-era scopeOf symbol mismatch that silently left agents tool-less. Event reads go through the public session.snapshotEvents() API and message construction uses a local, field-for-field equivalent of the host's createUserMessage.

Security

⚠️ This plugin exposes local execution capability (equivalent to RCE). It binds 127.0.0.1 only by default. When enabling:

  1. Set authToken — against other local processes and DNS-rebinding attacks (constant-time compare);
  2. Set workspaceRoots — constrain where agents may work;
  3. Never bind 0.0.0.0 or expose to LAN/WAN without a reverse proxy + TLS + auth.

Built-in guards: a Host-header allowlist (bind host + loopback aliases by default, guarding against DNS rebinding; a missing Host header gets 400) and a /mcp-only HTTP surface (everything else 404).

Provenance

The initial source of this project was copied from chushixixin/dsh-harness-mcp-server (MIT, thanks @chushixixin) and then evolved as an independent project — no git fork relationship, no upstream contributions planned. Key changes:

  • drops the Hermes-specific framing — targets any MCP client;
  • tracks current dsh releases (see Roadmap);
  • independent name and repository: dsh-ops-mcp.

Roadmap / known limitations (against dsh 0.1.5-rc.2)

The 0.2.0 compatibility issues were fixed in 0.3.0; 0.3.1 completed live-host E2E verification (all green — see docs/e2e-0.1.5-rc.2.zh.md) and fixed what it uncovered: the {{model}} prompt variable (model selection now completed via agentDefaultModel), turn-failure surfacing, pool-session flush, startup reattach off by default, and corrected install docs. 0.5.0 completed the model-selection surface: model_list (official catalog / llm fallback), per-call overrides on agent_run + task_inbox, select_model (in-session switch), reasoningEffort, the allowModelOverride gate, model reported in every result, and a session pool keyed by cwd + model.

What remains:

  • The task queue lives in process memory; a restart loses it (persistence is future work).
  • No server-side timeout or cancellation for agent_run / task_inbox — a hung agent holds its cwd's serial lock and later same-directory tasks queue behind it; callers should bring their own MCP-level timeout. The queue cannot be listed or cancelled either.
  • Read-only query surface is still incomplete: no session_list (list sessions, read history, read a session's current model) — only attach_session / rename_session / select_model.
  • preset remains deployment-level (one persona per MCP server instance); it cannot be chosen per call.
  • Tool calls inside spawned sessions go through the host approval policy (sensitive operations under ask may pop a dialog or fail closed; the read-only E2E operation was unaffected).
  • dsh_list_tools only lists the host-global registry; listing an agent's actually-visible tools needs a host-side API (the ScopeKey is a private symbol, unreachable under the zero-copy principle).
  • select_model requires the web profile's sessionController; where that service is absent (e.g. headless) only the catalog fallback and per-call overrides work, and the tool says so explicitly.
  • When dsh releases new versions, the @deepseek-ai/* devDependencies need syncing (compile-time only; the zero-runtime-dependency design is unaffected).

Development

npm install
npm run build    # standalone build (plain tsc) -> lib/
npm run smoke    # fake-ctx smoke on ports 8099/8098/8096/8095 (57 checks, real MCP protocol round-trips)
                 # + a port-conflict case (apply must fail loudly)

Live-host E2E (needs a local dsh with model credentials; costs a few tokens): boot a dedicated profile as described in docs/e2e-0.1.5-rc.2.zh.md, then run E2E_WITH_AGENT=1 node e2e.mjs.

License

MIT — see LICENSE (upstream copyright notice retained).