How do I use dsh-codebase-chat-mcp?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@dsh-codebase-chat-mcp explain how auth is handled in my codebase, with file and line citations" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

dsh-codebase-chat-mcp

by shinzarou-eng

Overview Schema Source Related Servers Discussions Admin

JavaScript

Local

Get started

npx dsh-codebase-chat-mcp setup

The wizard detects Claude, Cursor, Windsurf, VS Code, Zed, Gemini CLI, Kiro, Cline and Roo Code, asks how you want answers (host model, API key, or offline local model), writes the MCP config, done. No JSON to edit — and no API key: in promptOnly mode your host model does the thinking, or go fully offline with the embedded local model (localLlm) — no key, no host, no cloud.

Other paths — DeepSeek Harness plugin · CLI · from source · manual config: Reference.

Related MCP server: Ferret MCP

What a real session looks like

Run on this repository — the exact text the tools return:

$ npx dsh-codebase-chat --project . --health

== STATIC ANALYSIS — dsh-codebase-chat ==
Health score: 52/100 (D) · 33 files analyzed · 65 local imports

● Circular dependencies (0)
  none

● Unused files (candidates) (1)
  lib/client.js

● Unused exports (candidates) (45)
  lib/cache.js:21 — cachePath
  lib/index.js:2952 — normalizeLabels
  lib/index.js:2952 — getProjectName
  …

● Duplicate code blocks (2)
  12 lines × 2 files — lib/index.js, src/project.ts
  6 lines × 2 files — src/indexer.ts, src/retriever.ts

● Complexity hotspots (13)
  lib/index.js — score 418
  src/analysis.ts — score 81
  lib/client.js — score 55
  …

$ npx dsh-codebase-chat --project . --search "health score computation"

--- src/analysis.ts :: formatHealthReportMd (FUNCTION) [source: src/analysis.ts:285-353] ---
--- src/analysis.ts :: analyzeProject       (FUNCTION) [source: src/analysis.ts:149-232] ---
--- src/analysis.ts :: HealthReport         (TYPE)     [source: src/analysis.ts:15-26]   ---

$ npx dsh-codebase-chat --project . --ask "how is the index cached?"

> dsh-codebase-chat · prompt-only mode (no API key)
> Chunks: 81 · Tokens: 59,934 → handed to the host model
> Cite every technical claim with [source: relative/path:line].

codebase_health runs fully offline — deterministic, no LLM, same input → same score. Every answer from codebase_chat arrives with [source: file:line] receipts you can verify in seconds.

Why it wins

	Paste into a chat	Hosted assistant	dsh-codebase-chat
Sees your whole repo, not one file	❌	✅	✅
`[source: file:line]` citations	❌	~	✅
Code stays on your machine	❌	❌	✅
Inside Claude / Cursor / Windsurf	❌	~	✅
Deterministic health score, no LLM	❌	❌	✅
Answers fully offline (embedded LLM)	❌	❌	✅
Free — no API key, no account	~	❌	✅

How it works

/codebase-apply writes safely — dry-run · .dsh-backups/ before overwrite · protected paths · never outside the project.

The 13 tools

Understand	Decide	Act	Explore
`codebase_chat`	`codebase_intelligence`	`codebase_refactor`	`codebase_player`
`codebase_search`	`codebase_audit`	`codebase_tasks`	`codebase_crea`
`codebase_explain`	`codebase_report`
`codebase_health`	`codebase_ceo`
`codebase_impact`

Same engine, three surfaces: MCP tools in your IDE, slash commands in DeepSeek Harness, CLI flags anywhere. Every tool takes lang (fr/en), embed, promptOnly, localLlm, maxTokens.

Reference

DeepSeek Harness plugin

dsh plugin --profile web add dsh-codebase-chat

Then restart dsh web → http://127.0.0.1:3080 → Codebase Pro button.

CLI

npx dsh-codebase-chat --project C:\my-app --ask "how is auth handled?"
npx dsh-codebase-chat --project C:\my-app --health   # offline, no LLM
npx dsh-codebase-chat --project C:\my-app --health --diff main   # only what changed
npx dsh-codebase-chat --project C:\my-app --watch    # index stays hot while you code
npx dsh-codebase-chat --project C:\my-app --prompt intelligence   # same banner brief the IDE gets — pipe to any LLM

From source

git clone https://github.com/shinzarou-eng/dsh-codebase-chat.git
cd dsh-codebase-chat && pnpm install && pnpm build

Manual MCP config

{
  "mcpServers": {
    "dsh-codebase-chat": {
      "command": "npx",
      "args": ["dsh-codebase-chat-mcp"]
    }
  }
}

Without DEEPSEEK_API_KEY / OPENAI_API_KEY the server runs promptOnly. Set either key for direct-LLM calls — see mcp/README.md.

dsh --profile headless '/codebase "how is auth handled?" --project C:\my-app'
dsh --profile headless '/codebase-search "usePetStore" --project C:\my-app'
dsh --profile headless '/codebase-explain "storage.ts" --project C:\my-app'
dsh --profile headless '/codebase-refactor "split this hook" --file storage.ts --project C:\my-app'
dsh --profile headless '/codebase-intel --project C:\my-app'
dsh --profile headless '/codebase-audit --project C:\my-app --lang en'
dsh --profile headless '/codebase-tasks --project C:\my-app'
dsh --profile headless '/codebase-apply-tasks --project C:\my-app'
dsh --profile headless '/codebase-build --project C:\my-app'
dsh --profile headless '/codebase-git --project C:\my-app'

{
  "lang": "en",
  "maxTokens": 60000,
  "ignoreDirs": ["generated", "fixtures"],
  "ignoreFiles": ["bundle.js"],
  "ignoreGlobs": ["src/vendor/**", "*.snap"],
  "protectedPaths": ["src/locked", "migrations"]
}

Key	Effect
`lang`	Default prompt language (`en`/`fr`) — CLI, MCP tools, slash commands
`maxTokens`	Context budget when the caller passes none
`ignoreDirs` / `ignoreFiles`	Extra names skipped by indexing, `codebase_health`, file tree
`ignoreGlobs`	Globs on project-relative paths — `*` spans dirs, `` one segment
`protectedPaths`	Paths the apply pipeline can never patch

Variable	Default	Purpose
`CODEBASE_CACHE_DIR`	OS cache dir	Where the index cache lives
`DSH_PROJECT_ALIASES`	—	Extra `name=path` aliases (`;`-separated)
`DSH_DAKO_PROJECT`	—	Override the built-in `dako` alias
`DSH_PROTECTED_PATHS`	built-in list	Extra paths that can never be patched
`DEEPSEEK_API_KEY` / `OPENAI_API_KEY`	—	Direct-LLM mode only
`DEEPSEEK_BASE_URL` / `OPENAI_BASE_URL`	`https://api.deepseek.com/v1`	Custom endpoint
`CODEBASE_MODEL`	`deepseek-chat`	Model for direct-LLM mode
`CODEBASE_LOCAL_LLM`	—	`1` enables the embedded local model (offline answers); `hf:owner/repo:QUANT` or a `.gguf` path picks another model

Point it at a folder of code. Ask questions like a human — "How does login work?", "What should I fix first?" — in French or English. Every answer cites the exact file and line it came from. Nothing is uploaded anywhere.

Pointez-le vers un dossier de code. Posez vos questions en langage clair. Chaque réponse cite le fichier et la ligne exacts. Rien n'est envoyé sur internet.

Term	Meaning
MCP server	A plug format that lets AI assistants use extra tools. Install once — your IDE can "see" your code.
Prompt-only	The tool prepares the context; your existing AI writes the answer. No extra key, no extra cost.
Deterministic	Computed directly from your code — same input, same result, every time.

├── lib/            DeepSeek Harness plugin (index.js) + Codebase Pro UI (client.js)
├── src/            TypeScript engine — indexer, extractor, retriever, tokenizer, context, CLI
├── mcp/            Standalone MCP server package (dsh-codebase-chat-mcp)
├── test/           Vitest suites (extractor, retriever, tasks pipeline)
├── docs/           Landing page (GitHub Pages) + assets
└── dist/           Build output (tsup)

pnpm install && pnpm build && pnpm test && pnpm typecheck

Does it send my code to the cloud? Indexing, retrieval, and prompt building all run on your machine. In prompt-only mode the server makes no network calls itself — the assembled context is read by your host model (cloud or local, your choice). For zero-network answers end to end, enable the embedded local model (localLlm).

Do I need an API key? No — three ways to get answers: the host model (promptOnly, best quality), a DeepSeek/OpenAI key, or the embedded local model (localLlm, fully offline). The local model is small — great for quick lookups, prefer a hosted model for full reports. Inside DeepSeek Harness, the plugin uses your configured model.

Which languages are supported? French and English via lang on every tool. Source-side, AST covers JS/TS, Python, Go, Rust, Java, C#, PHP — the rest is indexed line by line.

Is applying patches safe? Yes. Dry-run, backups before overwrite, protected paths, writes stay inside the project.

EADDRINUSE on port 3080?

Get-NetTCPConnection -LocalPort 3080 | ForEach-Object { Stop-Process -Id $_.OwningProcess -Force }

Then restart dsh --profile web.


Shipped	tree-sitter AST (7 languages), deterministic health score, MCP setup wizard, `.codebase-chat.json`, `--diff` scoping, `--watch` mode, embedded local LLM
Next	GitHub Issues export from TASKS.md, prompt language packs (ES/DE/PT)
Planned	VS Code extension, HTTP/SSE transport, PR review mode, report export
Exploring	multi-repo workspaces, shared team index cache, CI bot

Full detail: ROADMAP.md

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