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Deepseek Delegate

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This MCP server exposes DeepSeek V4 to Codex as a single tool, enabling GPT Sol to delegate coding subtasks to DeepSeek for cheap execution.

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This MCP server exposes DeepSeek V4 to Codex as a single tool, enabling GPT Sol to delegate coding subtasks to DeepSeek for cheap execution.

README

A tiny local MCP server that exposes DeepSeek V4 to Codex as a single tool: call_deepseek_sub_agent.

It turns Codex into a hybrid agent: GPT Sol stays the architect (planning, reviewing, integrating) and DeepSeek V4 Flash does the cheap execution (boilerplate files, test-suite generation, bulk text transformation) at $0.14 per 1M input tokens.

How it works

┌────────────────────────┐   call_deepseek_sub_agent   ┌────────────────────────────┐
│  GPT Sol (Codex agent) │ ───────────────────────────▶ │  local MCP server (node)   │
│  plans / reviews /     │ ◀─────────────────────────── │  "deepseek-delegate"       │
│  integrates            │        output text          └─────────────┬──────────────┘
└────────────────────────┘                                          │ POST /responses
                                                                     ▼
                                                    DeepSeek API (api.deepseek.com)
                                                    deepseek-v4-flash / deepseek-v4-pro

Codex runs one model per session, so instead of switching providers mid-task you give Sol a delegation tool. Sol crafts a precise prompt, DeepSeek answers with plain text, and Sol reviews + applies the result. No file access is granted to DeepSeek — it only ever sees the exact prompt you send.

Features

  • Single MCP tool: call_deepseek_sub_agent (prompt required; model, system, temperature, max_output_tokens, reasoning_effort optional)
  • Uses DeepSeek's native Responses API
  • Zero extra key setup if you already use DeepSeek's official Codex integration
  • Works with Codex CLI, the ChatGPT desktop app, and the Codex IDE extension

Requirements

Quick start

1. Clone and install

git clone https://github.com/trixmix821/deepseek-delegate-mcp.git
cd deepseek-delegate-mcp
npm install

2. Register the MCP server

Add this to ~/.codex/config.toml (use the absolute path from step 1):

[mcp_servers.deepseek-delegate]
command = "node"
args = ["/absolute/path/to/deepseek-delegate-mcp/deepseek-mcp-server.mjs"]
env_vars = ["DEEPSEEK_API_KEY"]
tool_timeout_sec = 600
default_tools_approval_mode = "auto"

3. Provide your API key

The server looks for the key in this order:

  1. DEEPSEEK_API_KEY environment variable
  2. experimental_bearer_token under [model_providers.deepseek] in ~/.codex/config.toml (this is what DeepSeek's official Codex setup script writes — if you've run it, you're already done)
export DEEPSEEK_API_KEY=sk-...

4. Teach Sol to delegate

Append to ~/.codex/custom_instructions.md:

## Hybrid Architect: Sol (planner) + DeepSeek (executor)

You are the master architect (GPT Sol). You own the high-level plan, design,
and project structure. DeepSeek is your cheap execution layer.

For massive boilerplate files, extensive test-suite generation, bulk/repetitive
text transformation, or well-specified mechanical subtasks, invoke the
`call_deepseek_sub_agent` tool instead of doing the work in your own context.
Craft a precise, self-contained prompt: exact file paths, signatures, language,
framework, constraints, and expected output format. Never delegate open-ended
design decisions. Review DeepSeek's output, fix logic/interface mismatches, then
integrate. If you are already running as a DeepSeek model, do not delegate.

5. Verify

node test-deepseek.mjs "Reply with exactly: OK"

Expected output: the model replies OK, and a usage line ([deepseek-delegate] model=... input_tokens=... output_tokens=...) is printed to stderr.

Then restart Codex so it loads the new MCP server (in the TUI, /mcp shows active servers), and ask something like: "delegate the test-suite boilerplate to DeepSeek."

Tool reference

call_deepseek_sub_agent

Parameter Type Required Default Description
prompt string yes The exact coding instruction or context to process
model string no deepseek-v4-flash deepseek-v4-flash or deepseek-v4-pro
system string no Optional system prompt for the sub-agent
temperature number no 0.0–2.0 (no effect in thinking mode)
max_output_tokens number no 8192 Maximum output tokens
reasoning_effort string no low, high, or max
thinking boolean no off Force thinking mode on/off

Which model? deepseek-v4-flash is the default and right for nearly all delegated work (boilerplate, tests, transformations). Escalate to deepseek-v4-pro only when a single small task genuinely needs stronger reasoning — it costs ~3x more.

Configuration

Environment variables (all optional):

Variable Default Description
DEEPSEEK_API_KEY DeepSeek API key (falls back to your Codex config)
DEEPSEEK_MODEL deepseek-v4-flash Default model for the tool
DEEPSEEK_BASE_URL https://api.deepseek.com API base URL
DEEPSEEK_WIRE_API responses responses or chat (OpenAI-style chat completions)
DEEPSEEK_THINKING disabled enabled or disabled thinking mode default (disabled = fast/cheap)
DEEPSEEK_MAX_PROMPT_CHARS 30000 Reject prompts larger than this to prevent giant-payload delegation

Costs

DeepSeek V4 pricing (per 1M tokens, source):

Model Input (cache miss) Input (cache hit) Output
deepseek-v4-flash $0.14 $0.0028 $0.28
deepseek-v4-pro $0.435 $0.003625 $0.87

Context window is 1M tokens; max output is 384K.

Security notes

  • The server only calls the DeepSeek API. It never reads or writes your files, and DeepSeek only sees the text you put in the prompt.
  • DeepSeek's official setup stores your key in ~/.codex/config.toml in plaintext. Prefer export DEEPSEEK_API_KEY=... and keep the token out of the file.
  • default_tools_approval_mode = "auto" lets Sol call the tool without a prompt; change it to prompt if you want to approve every delegation.

Limitations

  • The tool only receives the prompt text — it has no access to your repository, so delegated prompts must be self-contained.
  • Delegation is only worth it for SMALL, mechanical, self-contained tasks. Prompts over 30,000 chars are rejected (configurable via DEEPSEEK_MAX_PROMPT_CHARS) — split them into smaller subtasks instead.
  • Thinking mode is off by default for speed; enable it via the thinking tool parameter only when the task genuinely needs reasoning.
  • Delegation is a judgment call by the agent. Explicitly asking for it ("delegate X to DeepSeek") makes it deterministic.
  • If your session is already running on DeepSeek, delegation is redundant.

License

MIT

from github.com/trixmix821/deepseek-delegate-mcp

Installing Deepseek Delegate

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/trixmix821/deepseek-delegate-mcp

FAQ

Is Deepseek Delegate MCP free?

Yes, Deepseek Delegate MCP is free — one-click install via Unyly at no cost.

Does Deepseek Delegate need an API key?

No, Deepseek Delegate runs without API keys or environment variables.

Is Deepseek Delegate hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Deepseek Delegate in Claude Desktop, Claude Code or Cursor?

Open Deepseek Delegate on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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