10 Best DeepSeek Harness Plugins for AI Developers in 2026

Introduction

DeepSeek Harness, known by its command-line alias dsh, is an agent runtime framework open-sourced by DeepSeek on August 13, 2026. It adopts an “everything as plugin” architecture. Models, tools, memory, sandboxes, and UI capabilities are all packaged as independent plugin components. As a result, the overall user experience is largely determined by plugin selection.

As of September 2026, the official GitHub repository has accumulated more than 22,000 stars. The community-curated awesome-dsh-plugin list includes 3,632 plugin entries sorted across 24 categories. The number of active plugins continues to rise. This article draws information from official documentation, community curated lists and hands-on testing notes. It selects 10 high-priority plugins, grouped into UI enhancement, tool capability, runtime support, web search, code review, knowledge base and other categories. For each plugin, it provides installation commands, target user groups, caveats, and configuration guidelines for connecting third-party model services. Users should carefully read plugin README files before installation. Plugins run with the same local permissions as the host user, a risk repeatedly emphasized by both official maintainers and community contributors.

The Expanding Ecosystem of DeepSeek Harness Plugins

The plugin ecosystem of DeepSeek Harness has grown from zero to thousands within a single month after open-source release. This scale outpaces the extension libraries of many comparable agent frameworks. According to GitHub statistics dated September 15, 2026, the official repository deepseek-ai/deepseek-harness holds 224,090 stars. The community awesome-dsh-plugin list tracks 3,632 plugins, and each entry must declare the dsh.bundle specification and support installation via the dsh plugin add command.

The table below breaks down plugin categories, counts and typical use cases as of September 2026:

The rapid expansion is backed by frequent official releases. @deepseek-ai/dsh updated to its 0.1.5 pre-release version on September 10, 2026. On the same day, DeepSeek launched the V4.1 Flash model and announced native Harness compatibility. This update introduced multi-modal input support, file uploads, sidebar controls and extended plugin entry points. The official README clearly warns that pre-release versions may contain breaking incompatible changes, so plugin selection should prioritize actively maintained projects.

Three Critical Concepts Before Installing Plugins

Before adding any DeepSeek Harness plugin, developers need to understand profile, permission scope and maintenance status. Missing these concepts often leads to runtime failures or security risks.

First, plugins attach to a profile. The dsh command uses profiles to isolate different runtime environments. The Web interface uses the web profile. The standard community installation syntax is dsh plugin --profile web add <package-name>. A global installation flag can be applied with npx @deepseek-ai/dsh plugin --profile web add <package-name>. Plugins take effect after restarting dsh web, and configuration can be adjusted in the settings panel.

Second, plugin permissions are equivalent to the local user account. The awesome-dsh-plugin disclaimer states plainly: community plugins execute third-party local code once installed. They can read files, consume network bandwidth and call local executables. A security audit published on August 28, 2026 analyzed roughly 1,100 dsh plugins and noted weak built-in sandbox enforcement. Some plugins can directly read stored API keys on the host machine. This is why model access plugins form a separate high-risk category in this guide.

Third, inclusion in the curated list is not equivalent to security audit. The selection rule for awesome-dsh-plugin is simple: plugins must install successfully, have truthful descriptions and remain under active maintenance. The curators do not perform rigorous code review or security vetting. All recommendations below come with applicable scenarios, and readers should selectively adopt plugins instead of installing the entire suite.

10 High-Priority DeepSeek Harness Plugins

The following 10 plugins cover eight common requirements for new adopters. Star counts and metadata are sourced from GitHub and the awesome-dsh-plugin public page on September 15, 2026.

Step 1: Start with dsh-market, the plugin marketplace

dsh-market is the native visual marketplace built inside DeepSeek Harness. The awesome-dsh-plugin list recommends it as the first plugin to install. It provides a card-based plugin gallery within settings, with tag filtering, one-click installation and version switching. All curated community plugins are discoverable through this marketplace.

dsh plugin --profile web add dshmarket

Users who prefer conversational workflows may install dsh-find-plugin. It allows the agent to search GitHub repositories tagged with dsh-plugin directly inside chat sessions.

open-design: Design and multimodal generation

open-design holds the highest star count among all DeepSeek Harness plugins. Positioned as an open-source alternative to Claude Design, this local-first desktop application converts agent prompts into design assets. It generates prototypes, presentation slides and system architecture diagrams. In September 2026, it announced native runtime compatibility with dsh. It supports structured design thinking, tool invocation, model preview, task cancellation and conversation recovery. Generated assets are previewed in real time within the open-design workspace. This plugin suits product, design and frontend developers; backend engineers can skip it if design assets are not required.

UI and Desktop: dsh-web full suite and DSH Desktop

The dsh-web full suite bundles standalone modules: task dashboards, remote mobile control, SSH operation panels, usage statistics and conversation archives. These modules attach to the dsh web runtime through the official profile mechanism without modifying core dsh source code.

dsh plugin --profile web add @linxin666/dsh-web-all@latest

Teams that want to skip Node.js environment configuration can adopt DSH Desktop maintained by anywhere-labs. It packages the web UI, backend service and plugin ecosystem as a native Windows and macOS application, ready to use after download. The repository clarifies it is an independent community project and has no official affiliation with DeepSeek. Two other desktop builds maintained by dataelement and hairyf also embed dsh-market and are available alternatives.

Memory: dsh-project-memory

dsh-project-memory delivers persistent project-level memory for DeepSeek Harness. Task checklists and file reading records are automatically saved as cross-session memory. Tasks and associated files maintain linkage, allowing developers to resume interrupted work after switching contexts. Text and code symbols are indexed during reading instead of full document scanning.

Alternative memory plugins include dsh-engram, which combines SQLite layered storage with full-text and vector search, and runtime36, which imports Obsidian vaults as agent knowledge bases.

Usage and Security: dsh-api-dashboard, dsh-plugin-gate and dsh-gov

dsh-api-dashboard displays balance information from DeepSeek,GLM, Kimi, MiniMax, OpenRouter and other platforms directly in the input box. It estimates token consumption for the current conversation and sub-agent calls, with billing calculated according to DeepSeek’s pricing rules. Users who exclusively use DeepSeek native APIs can switch to the lighter dsh-api-balance.

For security hardening, it is recommended to install two paired plugins:

• dsh-plugin-gate: Before executing dsh plugin add, it scans local directories and npm packages. It inspects install scripts, permission requirements, secrets and outbound network connections, returning BLOCK, WARN and PASS judgment levels.
• dsh-gov: Agent governance toolkit implementing allow, deny and ask tool permission modes. It outputs structured JSON audit logs and enforces per-agent token quota limits.

Web Search, Code Review and Knowledge Base

dsh-websearch distributes one query in parallel across Exa, DuckDuckGo, SearXNG, Brave, Tavily and 10 additional engines. Results are merged and deduplicated by URL. Users can toggle API key storage for search engines inside the settings panel. Those who only need default Tavily search may use dsh-plugin-tavily instead.

dsh-diff-approval aggregates every edit, write or str_replace_editor modification made by the agent into a change list. Users can retain or revert individual diff blocks, selected regions or full files. It provides side-by-side comparison views and is the core auditing tool for agent code changes.

@basabase/dsh-plugin appeared on Hacker News on September 10, 2026. It enables agents to read auditable knowledge bases and manipulate structured data. All write operations require manual human approval.

npx @deepseek-ai/dsh plugin --profile web add @basabase/dsh-plugin

This plugin requires Node.js version 24.18 or higher.

How to Select Plugins for Model & Account Access

Model connection plugins are not always mandatory. DeepSeek Harness’s native custom provider functionality can connect to any service compatible with OpenAI or Anthropic protocol. The official configuration documentation states that users select “add custom provider” in the model selector panel. Users fill in Provider ID, base URL, API protocol, secret key and at least one model ID. Supported protocols include openai-completions, openai-responses and anthropic-messages. Changes take effect on the next API request without service restart.

Multi-model platforms often require only one plugin to connect all models. Treerouter, functioning as an API gateway, provides unified model access endpoints compatible with this configuration pattern.

llm-pi-ai:
  providers:
    my-gateway:
      apikeyEnv: GATEWAY_API_KEY
      api: openai-completions
      baseURL: https://<your-platform-address>/v1
      models:
        - id: <model ID>
        - id: <vision model ID>

Model and account plugins address challenges that emerge after initial connectivity.

• dsh-llm-api-fill: Auto-fills missing context window length, token limits, reasoning capability and multimodal attributes for each model.
• dsh-model-pool: Aggregates multiple API keys. It automatically routes requests to the least exhausted key and enforces rate limit protection.
• dsh-adaptive-model-router: Detects and evaluates model quality tiers, routing subtasks to the most suitable large language model.

Installing and Managing Plugins

All DeepSeek Harness plugin management operations use the dsh plugin subcommand. The profile parameter determines which runtime instance receives the plugin.

# Launch web UI (default http://127.0.0.1:13080)
npx @deepseek-ai/dsh web

# Install plugin to web profile example: marketplace
dsh plugin --profile web add dshmarket

# Install web full suite
dsh plugin --profile web add @linxin666/dsh-web-all@latest

# Remove a plugin
dsh plugin --profile web remove <package-name>

Source installations require Node.js and pnpm. Run pnpm install and pnpm run build, then start pnpm dsh web. Desktop clients wrap the dsh plugin add/remove commands in GUI controls and do not require manual CLI operations.

Frequently Asked Questions

Q: What is the difference between DeepSeek Harness Skills and Claude Code Skills?

Skills are built into the dsh command specification. The skills plugin category packages tools as reusable components. These two systems are interchangeable in many scenarios.

Q: How to troubleshoot startup failures after installing plugins?

First check compatibility between plugin version and your current dsh release. Pre-release versions introduce frequent breaking changes. Test plugins in an isolated environment without API keys first. If the issue persists, remove the problematic plugin: dsh plugin --profile web remove <package-name>.

Q: How to judge whether a dsh plugin is secure?

Three checks are recommended: verify whether the repository is open-source and actively maintained; inspect package.json for dangerous postinstall scripts; check whether the plugin requests unnecessary outbound network access. dsh-plugin-gate automates these three preliminary checks, while dsh-plugin-audit performs deeper source, documentation and download lifecycle inspection. Test unfamiliar plugins in an environment without secrets and heavy business data.

Q: Can users without coding experience use DeepSeek Harness plugins?

Yes. Installing DSH Desktop or dataelement’s desktop release removes the requirement for manual Node environment setup. The built-in dsh-market supports one-click plugin installation. New users can use dsh-starter templates to build agent workflows from scratch with guided prompts.

Conclusion

For DeepSeek Harness users, selecting plugins is the first practical step toward building usable AI agents. A recommended minimal installation path starts with the marketplace plugin, followed by memory, usage tracking, security, code review and knowledge base plugins. The plugin ecosystem evolves quickly, and users should follow the awesome-dsh-plugin community registry. Pre-release software carries inherent risks; teams should separate experimental workloads from production services and maintain pinned plugin versions to prevent unexpected breaking changes. This article is built on public data published on September 15, 2026. Readers should regularly update plugin information to reflect new releases.

Learn more：https://treerouter.com