MIT-licensed, local-first cross-platform content discovery agent; connects to DeepSeek Harness via the companion DSH client plugin (dsh-openbiliclaw) as a 4th-column panel plus 22 Agent Bridge tools.
DSH integration
Compatible
Author-claimed
Safety audit
Unaudited
Last verified
2026-08-21
License
MIT
01What can it help you accomplish?
Use OpenBiliClaw's cross-platform personalized content discovery directly inside DeepSeek Harness
The OpenBiliClaw panel (recommendations / content library / chat / profile / settings) embedded as DSH's 4th column, plus 22 Agent Bridge tools that let DSH agents read recommendations, answer interest probes and close the learning loop
DeepSeek Harness users who want a personalized, local-first content feed alongside their agent work
Discover content across Bilibili, Xiaohongshu, Douyin, YouTube, X, Zhihu, Reddit, Linux.do, Bangumi, V2EX, Weibo and the open web from a single local agent
Cross-platform recommendations with friend-style explanations, unified into one candidate pool with diversity quotas and dedup
Users whose interests are fragmented across platforms and who want one recommendation agent instead of each platform's own feed
Keep the recommendation profile and all data fully local while tuning it via chat
A five-layer soul profile (MBTI, cognitive style, deep needs) and recommendation history stored only in local SQLite, updated by Socratic chat and feedback
Privacy-conscious users who refuse cloud recommendation profiles and want to own their data
02How to install into DeepSeek Harness
Prerequisites
- DeepSeek Harness installed (the DSH client plugin runs inside it)
- OpenBiliClaw backend deployed locally — desktop installers for macOS / Windows from Latest Release, or Python 3.11+ for script / manual deployment
- Your own LLM API key (LLM calls use your key by default); optional local Ollama + bge-m3 embedding
- A Chrome-compatible browser (Chrome / Edge / Brave / Arc / Vivaldi / Opera) or Safari (macOS) for the browser extension that connects platform login sessions
Installation steps
- 01
Deploy the OpenBiliClaw backend: download the desktop installer (macOS .dmg / Windows .exe) from the Latest Release page, or paste the one-line prompt from the README to an AI coding assistant for a customizable deployment
- 02
Install the DSH client plugin from the companion repository github.com/whiteguo233/dsh-openbiliclaw to bring OpenBiliClaw into DeepSeek Harness
- 03
In the browser with the extension installed, log in to Bilibili (default source) or opt in to Xiaohongshu / Douyin / YouTube / X / Zhihu / Reddit / Linux.do / V2EX / Weibo to initialize your profile
- 04
The DSH panel then works through the local backend API, with the 4th column and 22 Agent Bridge tools available in DSH
Verify the integration
Not specified by the author
03DSH integration and capability boundaries
Installed inside DeepSeek Harness via the companion DSH client plugin (dsh-openbiliclaw), which embeds the OpenBiliClaw panel as DSH's 4th column and registers 22 Agent Bridge tools
Cross-platform content discovery
Your logged-in platform sessions (via the browser extension) and opt-in source selection→Candidates from Bilibili / Xiaohongshu / Douyin / YouTube / X / Zhihu / Reddit / Linux.do / Bangumi / V2EX / Weibo / open web unified into one evaluated pool
Reads content from external platform sites using your existing browser login sessionsSends relevant content to the LLM / embedding providers you configureFive-layer soul profile with interest probes
Your cross-platform behavior, feedback and chat→A deep profile (MBTI, cognitive style, deep needs) plus proactive interest / avoidance probes that only become filters after confirmation
Writes profile and memory data to local SQLiteAgent Bridge for agent hosts (incl. DSH)
An agent host such as DeepSeek Harness / OpenClaw / Claude Code calling the versioned Agent Bridge→Proactive recommendations, interest probes, multi-turn durable chat, profile reads, on-demand multi-source recommendations and idempotent feedback write-back
Local-first storage & BYO LLM
Your own LLM API key (or experimental Codex CLI OAuth reuse); optional local Ollama + bge-m3 embedding→All behavior, recommendation, chat and profile data kept in local SQLite; no OpenBiliClaw-operated cloud account
Slim installers auto-download the bge-m3 vector model (~1.1GB) on first launchRequests are sent to the LLM / embedding endpoints you configure
04Who is it for? When not to use it?
Good for
- DeepSeek Harness users who want a personalized, local-first content feed alongside their agent work
- Users whose interests are fragmented across platforms and who want one recommendation agent instead of each platform's own feed
- Privacy-conscious users who refuse cloud recommendation profiles and want to own their data
Not for
- The DSH integration is not built into this repository: it ships as a separate client plugin in github.com/whiteguo233/dsh-openbiliclaw, and the OpenBiliClaw local backend must be running for the DSH panel to work.
- Desktop installers are experimental pre-releases: ad-hoc signed and not notarized, so macOS may block first launch and Windows SmartScreen may warn; the project itself notes this channel suits quick trials, not development.
05Compatibility, maintenance and safety notes
- The DSH integration is not built into this repository: it ships as a separate client plugin in github.com/whiteguo233/dsh-openbiliclaw, and the OpenBiliClaw local backend must be running for the DSH panel to work.
- Desktop installers are experimental pre-releases: ad-hoc signed and not notarized, so macOS may block first launch and Windows SmartScreen may warn; the project itself notes this channel suits quick trials, not development.
- The system relies on your own LLM key by default (built-in Gemini / DeepSeek / OpenAI / Claude / OpenRouter / Ollama or any OpenAI-compatible service), so model quota and cost are on you; background LLM budget caps and embedding circuit breaking exist precisely because unattended runs can burn quota.
MIT · actively maintained (latest release openbiliclaw-v0.3.208, 2026-08-18)
06Frequently asked questions
How does OpenBiliClaw connect to DeepSeek Harness?
Through a separate DSH client plugin published at github.com/whiteguo233/dsh-openbiliclaw. It installs OpenBiliClaw into DeepSeek Harness with a persistent 4th column (recommendations / content library / chat / profile / settings) and registers 22 Agent Bridge tools, so agents inside DSH can read recommendations, answer interest probes and feed back into the learning loop.
Is the integration native or MCP?
It is a DSH client plugin rather than a built-in runtime: the DSH panel talks only to the local OpenBiliClaw backend API, while the browser extension keeps handling platform login sessions and cookie sync.
What prerequisites do I need?
DeepSeek Harness itself, a running OpenBiliClaw local backend (desktop installers for macOS / Windows, or Python 3.11+ for script / manual deployment), your own LLM API key, and a Chrome-compatible browser (or Safari on macOS) with the OpenBiliClaw extension for connecting content platforms.
Where does my data go?
Default flow is browser extension → your local OpenBiliClaw backend → local SQLite; nothing goes to servers operated by the developers. If you configure cloud LLM / embedding services, relevant content is sent to those providers per your configuration.
Which platforms need login?
Bilibili, Xiaohongshu, Douyin, YouTube, X, Zhihu and Reddit work by reusing your existing browser login session via the extension. Linux.do, Bangumi, V2EX and Weibo can do public discovery anonymously; personal-signal initialization on them requires a logged-in session or public username.
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08Data and sources
新增 **DSH 客户端插件** —— 把 OpenBiliClaw 装进 [DeepSeek Harness](https://github.com/deepseek-ai/DeepSeek-Harness)：DSH 界面常驻第四栏（推荐…
以及把同一套面板搬进 DSH Web 界面的 [DSH 客户端插件](https://github.com/whiteguo233/dsh-openbiliclaw)（第四栏 + 22 个 Agent Bridge 工具）。桌面端、移动端…
This page is generated from the project’s public documentation, repository metadata and a structured parse of DSH Plugins; last verified on 2026-08-21. Found an error? Submit a correction.
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