@deepseek-ai/dsh-mcp-client

Minimal configuration

Add one entry per server; nothing else is required. After the harness starts, the server's tools appear in the model's tool list.

- id: mcp-github
  name: '@deepseek-ai/dsh-mcp-client'
  config:
    serverName: github
    transport: stdio
    command: npx
    args: ['-y', '@modelcontextprotocol/server-github']
    env:
      GITHUB_TOKEN: !!js process.env.GITHUB_TOKEN

- id: mcp-web
  name: '@deepseek-ai/dsh-mcp-client'
  config:
    serverName: web
    transport: streamable-http
    url: http://localhost:3000/mcp
    headers:
      Authorization: !!js '`Bearer ${process.env.MCP_TOKEN}`'

Field	Default	Meaning
transport	required	stdio or streamable-http
serverName	required	Namespace for the server's tool names; [A-Za-z0-9_-]{1,32}, unique inside one registration scope
command / args / env / cwd	—	stdio: executable, arguments, extra env merged over scrubbed ambient env, working directory
url / headers	—	streamable-http: endpoint URL and extra request headers
toolCallTimeoutMs	60,000	Timeout per tools/call invocation
failOnStartupError	false	Reject plugin activation when the initial connection or tool synchronization fails
reconnect.enabled	true	Reconnect automatically after a lost connection
reconnect.initialDelayMs	500	First reconnect delay; doubles per consecutive failed attempt
reconnect.maxDelayMs	30,000	Backoff ceiling; also the uptime after which the attempt budget resets
reconnect.maxAttempts	10	Consecutive failed attempts per outage before giving up

The generated configuration catalog is the exhaustive source for every accepted field.

After startup, the server's tools appear as mcp____ — try a prompt that uses one. If the initial connection fails, the harness still starts but no tools from that server appear, and an error is logged; set failOnStartupError: true to make a startup failure abort the harness instead.