DeepSeek Harness Plugin Guide

What are DeepSeek Harness plugins?

Composable capabilities inside the Harness runtime

DeepSeek Harness is an open-source agent harness from DeepSeek AI. Its official architecture treats components as plugins: a plugin can register services, tools, model providers, session behavior, user-interface elements, runtime hooks, or other capabilities through the shared context.

A repository in this directory is considered a DSH plugin when the community registry supplies a Harness install record and points to source intended for the plugin system. A package that only calls the DeepSeek API, integrates with another agent framework, or happens to include “DeepSeek” in its name belongs to a different ecosystem.

Core architecture

Context, reversible effects, profiles, and bundles

The Harness uses a Cordis context as the plugin boundary. A basic TypeScript plugin exports an apply(ctx) function. Registrations made through the context are scoped to the plugin lifecycle, so the runtime can clean them up when the plugin is disposed.

import type { Context } from '@deepseek-ai/dsh'

export function apply(ctx: Context) {
  ctx.effect(() => {
    // Start a resource or subscribe to an event.
    return () => {
      // Release that resource when the plugin stops.
    }
  })
}

Plugins can declare required services through injection and configuration through a typed Config shape plus a Schemastery schema. The official guide recommends validating configuration and failing loudly when required values are invalid.

Plugins and MCP

Choose the extension boundary that matches the job

The two can be combined. A Harness plugin may manage an MCP connection or expose client-specific controls around a portable MCP service. Prefer the smallest trust boundary that can satisfy the task, especially when filesystem access, shell execution, browser control, or credentials are involved.

When to use plugins

Start from the capability and its required access

Getting started

From a clean Harness profile to one reviewed plugin

1. 1
   Start the official Web experience

   Follow the current repository prerequisites, then run the command documented by DeepSeek AI.

   npx @deepseek-ai/dsh web

2. 2
   Configure a model and workspace

   In DSH Web, configure a model under Settings → Models and choose the workspace the agent may access.

3. 3
   Open the plugin source

   Match the GitHub owner, repository, package, bundle manifest, profile instructions, license, recent activity, and open compatibility reports.

4. 4
   Review the recorded install command

   A common community-registry form is shown below. Use the exact source and version recommended by the maintainer.

   dsh plugin --profile web add github:OWNER/REPOSITORY

5. 5
   Verify the narrow outcome

   Test one unfamiliar plugin at a time, inspect logs and network access, and confirm a recovery or removal path before relying on it.

Review and publish

Keep source identity, runtime effects, and recovery visible

This directory is an independent discovery surface. Inclusion, stars, and recent activity do not constitute a security audit, official endorsement, or a promise of compatibility.