# Knowledge Inbox > Local-first knowledge ingestion for AI agents and Obsidian - **Type:** MCP server - **Install:** `agentstack add mcp-lyc403223157-source-knowledge-inbox` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [lyc403223157-source](https://agentstack.voostack.com/s/lyc403223157-source) - **Installs:** 0 - **Category:** [Productivity](https://agentstack.voostack.com/c/productivity) - **Latest version:** 0.1.0 - **License:** Apache-2.0 - **Upstream author:** [lyc403223157-source](https://github.com/lyc403223157-source) - **Source:** https://github.com/lyc403223157-source/knowledge-inbox ## Install ```sh agentstack add mcp-lyc403223157-source-knowledge-inbox ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Knowledge Inbox **English** | [简体中文](README.zh-CN.md) Harness-neutral, local-first knowledge ingestion for Obsidian and other local retrieval tools. It turns links, text, videos, screenshots, PDFs, and local files into structured Markdown knowledge cards. Hermes, Codex, OpenClaw, and other MCP clients share the same adapters and processing service. > Current release: `0.3.0`. Web and file ingestion run cross-platform. WeChat Channels > downloading is an optional, experimental macOS integration that requires the desktop > WeChat client and a local TLS proxy. ## How it works ```text Hermes / Codex / OpenClaw / CLI / Web / Telegram | MCP / FastAPI | Source Adapter | ContentItem | Cleaner / OCR / Whisper / AI | Classifier / Tags / Knowledge Linker | Obsidian Markdown + SQLite ``` Every source is normalized into a `ContentItem`. To add a platform, implement `SourceAdapter.detect()` and `SourceAdapter.fetch()`, then register the adapter in `backend/adapters/registry.py`. ## Supported sources | Source | Input | Capabilities | | --- | --- | --- | | Web pages, blogs, and news | URL | Readability extraction, Markdown conversion, and image download | | WeChat Official Accounts | URL | Article body, author, and images; can also be synced by another tool | | X / Twitter | Post URL | Current post, visible parent context, quoted content, and media when available | | YouTube | URL | Captions first; Whisper fallback when captions are unavailable | | Podcast RSS and Apple Podcasts | Feed or episode URL | Episode metadata, Podcasting 2.0 transcript, audio download, and Whisper fallback | | Vimeo | URL | oEmbed metadata, captions when available, and Whisper fallback | | Direct audio, video, and HLS | Media URL | Streaming download for common media files; yt-dlp resolution for `.m3u8` | | PDF | File | Text extraction; OCR for scanned pages with the media extra | | Images | File | OCR plus visual and chart descriptions when a vision model is configured | | Audio and video | File | Whisper transcription or vision-model understanding | | WeChat Channels | Share URL | Experimental macOS integration, or upload the original video directly | | Telegram | Webhook | Text, captions, or the first URL found in a message | ## Quick start Python 3.11 or newer is required. Media processing requires `ffmpeg`; OCR requires Tesseract. ```bash python3 -m venv .venv source .venv/bin/activate pip install -e ".[media,browser,mcp,dev]" playwright install chromium cp config.example.yaml config.yaml uvicorn backend.main:app --host 127.0.0.1 --port 8787 ``` Open for the universal inbox: paste a link or text, or drop a video, screenshot, PDF, or local file into the same input area. Source detection, AI processing, classification, tags, linking, and Obsidian output are automatic. Use the **EN / 中** button to switch the web interface. Completed entries under **Recently generated** can be clicked to open their knowledge-card folder in the system file manager. On first launch on macOS, choose an existing Obsidian Vault or Markdown folder with the native folder picker, then choose the card subfolder. The service verifies write access and stores only these two values in the ignored local file `data/storage.yaml`. Use **Settings** later to change them. When `OBSIDIAN_VAULT_DIR` is set by Docker or an administrator, the web setting is read-only. Other host platforms can use the absolute-path fallback in the same dialog. On mobile, the primary workflow is Telegram, Discord, or another IM connected to an Agent Harness. Forward a standalone link or file and the Harness calls `knowledge_ingest`; no web form or extra “save this” message is required. Links included as context for ordinary questions are not archived automatically. A browser extension for one-click desktop capture is a natural next client, but is not included yet. You can also use the CLI: ```bash .venv/bin/python scripts/ingest.py 'https://example.com/article' .venv/bin/python scripts/ingest.py 'https://feeds.example.com/show.rss' .venv/bin/python scripts/ingest.py 'https://vimeo.com/123456' .venv/bin/python scripts/ingest.py '/absolute/path/file.pdf' .venv/bin/python scripts/ingest.py 'A note to keep' --title 'Quick note' ``` The same pipeline is available through the API: ```bash curl -X POST http://127.0.0.1:8787/api/ingest \ -H 'content-type: application/json' \ -d '{"url":"https://example.com/article"}' ``` ## Configure AI and Obsidian The AI layer uses an OpenAI-compatible Chat Completions endpoint. AI is disabled by default; without a model the system still creates a local fallback summary. Enable AI for classification, visual understanding, and richer tags: ```bash export OBSIDIAN_VAULT_DIR=/absolute/path/to/ObsidianVault export AI_ENABLED=true export OPENAI_BASE_URL=http://127.0.0.1:11434/v1 export OPENAI_API_KEY='' export OPENAI_MODEL=qwen2.5:7b export OPENAI_VISION_MODEL=your-vision-model ``` You can set the same values in `config.yaml`. The config file, `.env`, database, browser login state, and downloaded media are ignored by Git. Knowledge linking uses `qmd` when available. If `qmd` is not installed, it falls back to lexical matching over the latest 1,000 Markdown notes in the Vault. Cards are written to a temporary file and atomically replaced so an indexer never sees a partial note. ## MCP tools and Harness clients `scripts/knowledge_mcp.py` is a harness-neutral stdio MCP server. It exposes: - `knowledge_ingest`: ingest a URL, local file, or text and wait for the knowledge card to finish. - `knowledge_get_job`: inspect the current state of a known ingestion job. - `knowledge_list_capabilities`: list supported sources and input types. - `knowledge_wechat_prepare`: refresh the local WeChat Channels window only when the client connection needs recovery. Each Harness launches the same server with a Python environment that includes the `hermes` extra and the absolute path to `scripts/knowledge_mcp.py`. Client-specific Skills are in `clients/hermes`, `clients/codex`, and `clients/openclaw`; they contain routing guidance, not duplicate adapters. See `clients/README.md` for installation commands. ## Docker ```bash cp .env.example .env docker compose up --build ``` Docker is suitable for web pages, files, OCR, transcription, and the AI pipeline. When the workflow needs the macOS WeChat client, system proxy, or a GUI browser login, run the backend directly on the host. Compose binds the service to `127.0.0.1:8787`. ## WeChat Channels security boundary The Channels integration uses the separately maintained [`ltaoo/wx_channels_download`](https://github.com/ltaoo/wx_channels_download) project. Its license and security boundary are separate from this repository. This project does not distribute its binary, root certificate, cookies, or WeChat login data. See `integrations/wechat-channels/README.md` for installation, licensing, proxy, and macOS permission details. The downloader creates a local TLS proxy. Use only a trusted, checksum-verified build and never expose the downloader or this service to a LAN. The MCP tool temporarily switches the HTTP/HTTPS proxy for the task and restores the previous settings afterward. The original video is deleted only after both the Obsidian note and SQLite record have been written successfully. ## Verification ```bash pytest -q ruff check backend scripts tests ``` The test suite covers Markdown formatting, task recovery, text end-to-end ingestion, X context, the WeChat Channels adapter, video transcoding, post-write cleanup, and input classification. Real platform pages and login sessions change over time, so production deployments should still perform a separate end-to-end check for each platform they use. ## Contributing and license Read `CONTRIBUTING.md` and `SECURITY.md` before submitting a change. Original project code is licensed under Apache-2.0. Optional third-party components remain under their own licenses; see `THIRD_PARTY_NOTICES.md`. ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [lyc403223157-source](https://github.com/lyc403223157-source) - **Source:** [lyc403223157-source/knowledge-inbox](https://github.com/lyc403223157-source/knowledge-inbox) - **License:** Apache-2.0 Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** yes - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** yes - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-lyc403223157-source-knowledge-inbox - Seller: https://agentstack.voostack.com/s/lyc403223157-source - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.