deepseek-mcp

A local MCP server that makes DeepSeek available to your primary coding agent for code review and second opinions.

The server reads the repo itself. Your agent passes a git ref or a list of paths — never the code — so a review costs about twenty tokens on the way in instead of several thousand.

Tools

All three are read-only and take paths, not content.

Related MCP server: ProjectBrain

Install

npm i -g @berrydev-ai/deepseek-mcp

That puts a deepseek-mcp binary on your PATH; no checkout needed. Or skip the install and let your MCP client fetch it on demand with npx -y @berrydev-ai/deepseek-mcp, at the cost of a slower cold start.

One caveat if you install from source instead: avoid npm i -g git+https://github.com/berrydev-ai/deepseek-mcp.git. On npm 10.x it appears to succeed but symlinks the global package at a bare clone in the cache with no working tree, leaving bin dangling. Use the registry, or a tarball. dist/ is committed so that installing from git or a tarball still works — a global install has no devDependencies, so nothing can compile at install time.

Configure

There is no dotenv loader. The server reads process.env and nothing else, so .env is a reference for what to set rather than a file that gets read. Configuration belongs in your MCP client's env block.

Claude Code

claude mcp add deepseek -s user -e DEEPSEEK_API_KEY=sk-... -- deepseek-mcp

-s user registers it across all your projects. Without it the default is local scope, which is limited to the directory you ran the command in.

Codex

codex mcp add deepseek --env DEEPSEEK_API_KEY=sk-... -- deepseek-mcp

Note --env rather than Claude's -e, and that the command to launch goes after -- in both. Codex writes to ~/.codex/config.toml globally, so there is no scope flag to think about. The equivalent by hand:

[mcp_servers.deepseek]
command = "deepseek-mcp"

[mcp_servers.deepseek.env]
DEEPSEEK_API_KEY = "sk-..."

Verify with codex mcp get deepseek, and codex mcp remove deepseek to undo.

Any other MCP client

{
  "mcpServers": {
    "deepseek": {
      "command": "deepseek-mcp",
      "env": {
        "DEEPSEEK_API_KEY": "sk-..."
      }
    }
  }
}

Note that a missing key does not stop the server from starting, so the client will report it as connected either way — assertConfigured only fires on the first tool call. If every call comes back with "DEEPSEEK_API_KEY is not set", the env block is the place to look.

The server operates on its working directory, which is normally your project. Set DEEPSEEK_REPO_ROOT to override.

Local development

git clone https://github.com/berrydev-ai/deepseek-mcp.git
cd deepseek-mcp && npm install && npm run build

Run npm run build and commit dist/ alongside any source change, otherwise installs keep serving the previous build.

Direct or through AI Gateway

One env var, no code change. https://api.deepseek.com is the default and has no dependencies. Pointing DEEPSEEK_BASE_URL at a Cloudflare AI Gateway endpoint instead gets you request logs, spend caps, caching and the ability to swap models without touching this repo — worth it the moment you want to compare two models on the same review.

Tuning the prompts

prompts/review.md and prompts/consult.md are the entire behaviour of the server. They are plain markdown; edit and restart. Both are written to keep output tight, because whatever DeepSeek returns lands in your primary agent's context window and competes with everything else there.

The review prompt enforces severity grouping and file:line anchors, and forbids restating what the code does. If reviews come back vague, the fix is almost always in that file rather than in the TypeScript.

Getting it actually invoked

The most common failure mode is not a bug — it is that the primary agent never calls the tool. Coding agents are reluctant to delegate. The tool descriptions are written to draw a clear line (substantial changes yes, one-line edits no), but you may still need to ask for it explicitly at first, or add a line to your CLAUDE.md telling the agent to get a DeepSeek review before opening a PR.

Delegation only pays for itself on work that involves reading and analysing real amounts of code. On small tasks the per-call overhead dominates.

Guards

• Paths are resolved and rejected if they escape the repo root.

• Git refs are validated so an argument cannot be smuggled in as an option.

• Input is truncated at a character budget, and the response says when that happened.

• Model calls abort at 55s, below the ~60s tool-call timeout most clients enforce, so you get a clear message rather than a hang.

• Every response carries a footer with file count, model and token usage.

Notes

Built on @modelcontextprotocol/server v2 via serveStdio, which serves both the 2025 and 2026-07-28 protocol revisions from one factory — clients on either revision work without configuration.

Model defaults are deepseek-v4-flash for reviews and deepseek-v4-pro for consults. Check them against whichever endpoint you point at — the names move over time.

Watch out for the older deepseek-chat and deepseek-reasoner names. They still return 200, but the response comes back as deepseek-v4-flash, so a stale value costs you the reasoning model without ever raising an error. The model in the response footer is read from the provider's reply rather than from your config, so it will tell you what actually ran.

License

MIT — see LICENSE.