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dsh-web-mcp

๐Ÿค– AI-assisted project ยท A college student's learning project, with significant code generated by an LLM agent under human direction and review.

License: MIT Python 3.10+ MCP

MCP bridge for DeepSeek Harness (DSH) web UI โ€” exposes the cordis RPC API over HTTP /api/<endpoint> as stdio MCP tools. Any MCP client (Codex CLI, Claude Desktop, etc.) can drive DSH sessions and benefit from prompt-prefix cache reuse.

๐ŸŒ ไธญๆ–‡ๆ–‡ๆกฃ๏ผšREADME.zh.md

What is in the box

Eight tools, all backed by DSH web's cordis RPC over HTTP /api/<endpoint>:

Tool

Purpose

dsh_list_workspaces

Enumerate every workspace known to the running DSH web UI.

dsh_create_session

Adopt a directory (creating the workspace if missing), then create a session bound to it. Selects the model in one shot. Returns sessionId.

dsh_send_message

Send a prompt and block until the assistant turn completes. Returns the assistant text plus per-turn token usage including cacheReadTokens / cacheWriteTokens. When the agent requests permission, it answers via an MCP sampling callback (see below) so the turn keeps running.

dsh_wait_turn

Wait for the in-flight turn to finish without sending a new prompt. Use it after answering a pending approval.

dsh_list_pending_approvals

List still-pending approval requests (approvalId, toolName, callId?, reason?, rpcId), optionally filtered by session_id.

dsh_respond_approval

Answer one pending approval (allowed-once / rejected); returns the DSH receipt (accepted: true = the answer was consumed).

dsh_get_session_stats

Fetch cached projections: tokenUsage, sessionStats, contextPressure.

dsh_resume_session

Verify a session is still alive and surface its current model. Subsequent dsh_send_message calls reuse the prompt prefix.

Related MCP server: dsh-ops-mcp

Approval callback (ๆƒ้™ๅฎกๆ‰นๅ›ž่ฐƒ)

DSH agents ask for permission before sensitive tool calls (e.g. a sandbox escalation to danger-full-access). The request surfaces in the session log as approval/asked and โ€” on the DSH web event stream โ€” as an answerable approval/requested frame. This bridge turns that into a two-track callback:

  1. Sampling callback (default, works with Hermes CN Desktop โ‰ฅ 0.18): while dsh_send_message / dsh_wait_turn are waiting for the turn, the server sends the client a sampling/createMessage request describing the tool and the DSH-provided reason; the client's answer (allowed-once / rejected) is posted back to DSH via POST /api/respond and the turn continues. Hermes supports this out of the box (sampling enabled by default; see its Native MCP docs). Sampling needs to run inside an MCP request, so it is only active on the real MCP transport.

  2. Tool fallback (works with any MCP client): set auto_respond_approvals=false on dsh_send_message (or sampling fails / is unavailable), and the call returns immediately with awaitingApproval: true + pendingApprovals instead of waiting. The caller (or a human) then decides:

    dsh_send_message(...)                    -> {"awaitingApproval": true, "pendingApprovals": [...]}
    dsh_respond_approval(session_id, <approvalId>, "allowed-once")   -> {"accepted": true}
    dsh_wait_turn(session_id, ...)           -> normal turn result

    dsh_list_pending_approvals lists whatever is still pending at any moment (the DSH event stream replays every unanswered approval on connect).

Wire facts (verified against DSH source and a live probe): the answer must echo the rpcId of the approval/requested frame โ€” a fresh UUID minted by the host's pending table, not the audit approvalId โ€” and the payload must carry the matching approvalId. The event stream is a WebSocket (GET /api/events.mux; plain HTTP gets 426), which is why the websockets package is a hard dependency.

Requirements

  • Python 3.10+

  • A running dsh web instance on http://127.0.0.1:3080 (override with DSH_BASE_URL)

  • uv (recommended) or pip

  • websockets (installed by uv sync; needed for the approval event stream)

Install

git clone https://github.com/cv588888888888888888888ju/dsh-web-mcp.git
cd dsh-web-mcp
uv sync

Then run as a stdio MCP server:

uv run dsh-web-mcp

Wire up Hermes Agent

Register with hermes mcp add:

hermes mcp add dsh --command uv --args --directory C:\Users\chenty\Documents\feishu-bot\dsh-mcp run dsh-web-mcp

โš ๏ธ Known pitfall (tested):

  • Do not pass --env DSH_BASE_URL=... โ€” it gets forwarded to dsh-web-mcp's argparse and fails with unrecognized arguments. Set DSH_BASE_URL as a user/system environment variable instead.

  • A new session is required after registering (config loads at session start).

  • If prompted Enable all 8 tools? [Y/n/select], answer Y.

Wire up Codex CLI

Edit %USERPROFILE%\.codex\config.toml (or ~/.codex/config.toml on other OS):

[mcp_servers.dsh]
command = "uv"
args = ["--directory", "C:\\path\\to\\dsh-web-mcp", "run", "dsh-web-mcp"]

# Optional, defaults to http://127.0.0.1:3080 if omitted
[mcp_servers.dsh.env]
DSH_BASE_URL = "http://127.0.0.1:3080"

Restart Codex CLI. The eight dsh_* tools appear alongside the built-in tools.

Probe

probe.py is a developer-side smoke test that exercises all tools end-to-end against the running DSH web UI โ€” including the approval chain (trigger a real approval, answer it with accepted: true, and wait for the turn to finish):

uv run python probe.py

It prints a JSON blob per step; expected outcome is

{
  "ok": true,
  "step": "send_message",
  "reply_contains": "TASK_OK",
  "cacheReadTokens": 8192
}

The approval steps report send_message_awaiting_approval, respond_approval (accepted: true), and wait_turn_after_approval (reply_contains: "APPROVAL_OK").

Failure modes

  • DSH web not reachable โ€” the server starts but every tool returns {"ok": false, "error": "DSH web not reachable at ..."}. Make sure dsh web is running (dsh web --port 3080).

  • DSH schema drift (rc.X โ†’ rc.Y) โ€” unknown field errors come back as {ok: false, error: "dsh returned <code>: <msg>"}. The model schema in models.py is intentionally extra="allow" so additional fields pass through; reported mis-parses should be filed against models.py.

  • Prompt timeout โ€” dsh_send_message times out after timeout_s (default 120s); rerun with a larger value if your prompt is long. An approval that nobody answers also holds the turn: use dsh_list_pending_approvals / dsh_respond_approval (or wait for the human in the DSH web UI) and then dsh_wait_turn.

  • Sampling unavailable โ€” outside an MCP request (e.g. probe.py) or with a client that does not implement sampling/createMessage, dsh_send_message falls back to returning awaitingApproval: true with pendingApprovals; use the tool fallback above.

Configuration

Environment variables read by dsh-web-mcp:

Var

Default

Description

DSH_BASE_URL

http://127.0.0.1:3080

DSH web base URL.

DSH_TIMEOUT_S

60

Per-request timeout in seconds (generous; a single LLM turn may take ~30s).

DSH_MCP_LOG

INFO

Python logging level (use DEBUG to see wire-level traffic).

CLI flags mirror the env vars: --base-url, --timeout, --check.

Why this exists

By default Codex CLI talks to the OpenAI / Azure providers directly. When MCP routing through DSH, the deepseek-v4-flash preset in DSH keeps system + tools + conversation prefix cached, so every subsequent turn in the same session reads 8K+ cached tokens and only pays uncached input for the new prompt + uncached output for the new reply โ€” measured per tokenUsage.cacheReadTokens in dsh_send_message results.

Background

This project was built as a learning exercise by an undergraduate student exploring agent tooling. The bulk of the code was generated by an LLM coding agent (Codex CLI + DeepSeek) under human direction; every line was reviewed and the behavior verified end-to-end before publication. Bugs are likely given the author's experience level โ€” please open issues.

Status

Pre-release. API surface follows DSH 0.1.0-rc.6 schema (rpc-map.d.ts); regenerate from source if you bump DSH.

License

MIT

Available Tools

5 tools
dsh_create_sessionA

Create a new DSH session bound to a directory; auto-creates the workspace if missing. Returns the sessionId for follow-up tool calls.

Inputs: model, provider, workspace_path, reasoning_effort.

dsh_get_session_statsB

Fetch cached projections (tokenUsage, sessionStats, contextPressure) for a DSH session.

Inputs: session_id.

dsh_list_workspacesA

List every DSH workspace known to the local dsh web UI.

Inputs: no named parameters.

dsh_resume_sessionA

Re-load an existing DSH session and verify its cached state. Subsequent dsh_send_message calls reuse the prompt prefix.

Inputs: session_id.

dsh_send_messageB

Send a prompt to a DSH session and block until the assistant turn completes. Result includes assistant text and token usage (cacheReadTokens / cacheWriteTokens).

Inputs: prompt, timeout_s, session_id, poll_interval_s.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelogโ€ฆ

    TDQS

    A3.8/5.0

    Scored across 5 tools

    Disambiguation4/5

    Tool purposes are mostly distinct, but create_session and resume_session both establish a session for sending messages, and the difference (new vs existing) could confuse an agent without careful reading. Descriptions resolve the ambiguity, so only minor overlap remains.

    Naming Consistency5/5

    All tools share the dsh_ prefix and follow a clean verb_noun pattern: create_session, send_message, get_session_stats, resume_session, list_workspaces. The naming is perfectly consistent and predictable.

    Tool Count5/5

    With 5 tools, the server is well-scoped for session and workspace management. Each tool has a clear role, and the count is within the ideal range for a purpose-built MCP.

    Completeness3/5

    Core workflow is covered (create/resume, send, stats, list workspaces), but the surface lacks session deletion or a way to list existing sessions directly. These are notable lifecycle gaps that agents may hit when trying to manage or clean up sessions.

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