# Root Kg > Your knowledge graph. Ask questions across all your notes, meetings, and emails — cited answers. - **Type:** MCP server - **Install:** `agentstack add mcp-mshadmanrahman-root-kg` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [mshadmanrahman](https://agentstack.voostack.com/s/mshadmanrahman) - **Installs:** 0 - **Category:** [Databases](https://agentstack.voostack.com/c/databases) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [mshadmanrahman](https://github.com/mshadmanrahman) - **Source:** https://github.com/mshadmanrahman/root-kg - **Website:** https://github.com/mshadmanrahman/root-kg ## Install ```sh agentstack add mcp-mshadmanrahman-root-kg ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About ROOT Ask questions across all your knowledge. Get cited answers. Turn your Obsidian vault, meeting notes, and emails into a queryable intelligence layer. What You Can Ask • How It Works • Quick Start • Tools • Running Costs • Comparison --- You wrote it down. You know you did. It was in a meeting note, or maybe a Slack thread you copied into Obsidian, or that document you made before the planning session. But now you're searching and finding nothing, or finding five things that contradict each other, and you're holding the whole mental model in your head again. ROOT fixes this. It connects your notes, meetings, and emails into a single queryable layer - one you can ask questions in plain English, the same way you'd ask a colleague who'd read everything you've ever written. ``` > root_ask("What decisions were made about the Search Redesign?") # ROOT Answer Leadership APPROVED the Search Redesign project on March 17, 2026. Scope and priorities were locked and finalized at the kick-off meeting on March 23. Scope: consolidate 1,200 product categories down to 85 across 12 groups, based on the industry taxonomy. Owner: Alex Chen (coordinator), Jordan / Sam (engineering). Sprint start: April 7. *Based on 5 search results and 2 entity matches.* ``` That answer came from five different notes and two separate meetings. No manual searching. No context-switching. ROOT found the thread, traced the decisions, and told you what happened. --- ## What You Can Ask ROOT ROOT is built for the questions that currently require you to open six tabs and reconstruct things from memory: - "What did I commit to Ric last week?" - "How did the pricing decision evolve over the last month?" - "Who has been working on Project X, and through what?" - "What did the team decide about the API design, and did it change?" - "What action items from last quarter are still open?" - "Brief me on this person before my 1:1 - everything we've discussed." You ask in plain English. ROOT synthesizes an answer with citations from every source it has indexed. --- ## What Makes It Different From Searching Obsidian | Obsidian search | ROOT | |----------------|------| | Keyword matching | Semantic understanding ("lead decline" finds "traffic drop" notes) | | Shows files | Shows synthesized answers with citations | | No entity awareness | Knows people, projects, decisions as first-class objects | | No cross-source | Combines vault + meetings + emails + Slack | | Manual navigation | Traverses relationship graph automatically | | One note at a time | Aggregates across hundreds of notes per query | ROOT knows that "Alex" from the kick-off meeting is the same "Alex Chen" from the planning session. It knows she is connected to "Sam" via an implementation dependency. You can traverse these connections across hundreds of notes without opening a single file. --- ## Quick Start ```bash # Clone and setup git clone https://github.com/mshadmanrahman/root-kg.git cd root-kg python -m venv .venv && source .venv/bin/activate pip install -e . # Interactive setup wizard python -m root init # Index your notes (~2 min for 2,500 notes) python indexer.py # Extract entities (~$3 on Anthropic Haiku, or free with Ollama) python indexer.py --extract # Register as MCP server in Claude Code claude mcp add root -- python server.py # Try it # root_search("your topic") # root_ask("your question") # root_graph("person name", 2) ``` > ROOT connects to Claude Code as an MCP server. New to Claude Code? [claudecodeguide.dev](https://claudecodeguide.dev) gets you set up in under an hour. --- ## Running Costs This is almost free to run. The initial setup costs a few dollars. After that, daily operation runs in the pennies - because ROOT only reprocesses notes that have actually changed. | Activity | Frequency | Cost | |----------|-----------|------| | Initial vault index (embeddings) | Once | $0 (local model) | | Initial entity extraction | Once (~2,500 notes) | ~$3-5 (Haiku) or $0 (Ollama) | | Incremental re-index | Every 2 hours | $0 (local) | | Incremental extraction | Every 2 hours, only changed notes | ~$0.01-0.05/day | | Queries via root_ask | On-demand | ~$0.01/query (Sonnet) | | **Monthly estimate** | | **$1-3** | Compare that to Mem.ai ($20/mo) or Rewind ($20/mo) - both cloud-only, both proprietary. ROOT runs locally, costs a latte per month, and your data never leaves your machine unless you choose a cloud LLM for synthesis. --- ## How It Works ROOT has a four-step pipeline: ingest, embed, extract, query. ``` ┌──────────────────────────────────────────────────────────────┐ │ DATA SOURCES │ │ │ │ Obsidian Vault meetings (Granola) emails │ │ 2,500+ notes auto or manual Gmail MCP │ │ auto every 2h via root_ingest via ingest │ └──────────────┬───────────────┬───────────────┬───────────────┘ │ │ │ ▼ ▼ ▼ ┌──────────────────────────────────────────────────────────────┐ │ STEP 1: INDEXING (free, runs locally) │ │ │ │ Content hashing (SHA-256) for incremental updates │ │ Markdown-aware chunking (splits on headings) │ │ Local embeddings: all-MiniLM-L6-v2 (384 dims, CPU) │ │ Stored in SQLite + sqlite-vec │ │ │ │ Cost: $0. No API calls. ~2 min for 2,500 notes. │ └──────────────┬───────────────────────────────────────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ STEP 2: ENTITY EXTRACTION (pennies/day) │ │ │ │ For each new/changed note, an LLM extracts: │ │ │ │ Entities: people, projects, decisions, events, │ │ concepts, organizations │ │ Relations: works_with, owns, decided, discussed, │ │ blocked_by, depends_on, manages, etc. │ │ Confidence: 0.9+ explicit, 0.7 implied, 0.5 weak signals │ │ Aliases: "Fredrik" = "Frederick", "FoS" = "Field of Study" │ │ │ │ Model: Claude Haiku (~$0.003 per note) │ │ Daily cost: pennies (only changed notes reprocessed) │ └──────────────┬───────────────────────────────────────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ STEP 3: KNOWLEDGE GRAPH (stored in SQLite) │ │ │ │ ┌───────────┐ ┌────────────┐ ┌────────────┐ │ │ │ entities │────▶│ relations │◀────│ aliases │ │ │ │ 13,000+ │ │ 20,000+ │ │ 8,000+ │ │ │ └───────────┘ └────────────┘ └────────────┘ │ │ │ │ │ ▼ │ │ ┌──────────────┐ ┌───────────────┐ │ │ │ entity-note │ │ notes │ │ │ │ links │ │ with chunks │ │ │ │ 28,000+ │ │ & embeddings │ │ │ └──────────────┘ └───────────────┘ │ │ │ │ Graph traversal via recursive CTEs. ### The Two-Model Strategy - **Haiku** ($0.80/$4 per MTok): bulk extraction. Runs on every note, cheap enough to process thousands. - **Sonnet** ($3/$15 per MTok): synthesis. Only runs when you ask a question. Higher quality reasoning for connecting dots. Embeddings are always free and local. Only entity extraction and `root_ask` use the LLM. --- ## 18 MCP Tools ### Search & Discovery ``` root_search(query) Semantic search across all notes root_search_folder(query, dir) Search within a specific folder root_note(path) Read full note content root_stats() Index health and statistics root_connections(path) Cross-domain connections for a note root_themes(scope) Recurring themes via clustering root_gaps(topic) Knowledge gaps and blind spots ``` ### Multi-Source Intelligence ``` root_ingest(source, title, content) Ingest from any MCP source root_ingest_batch(items) Batch ingest root_about(person) Everything about a person root_open_loops(scope) Unfollowed action items root_project_pulse(project) Activity pulse for a project ``` ### Entity Graph & GraphRAG ``` root_graph(entity, depth) Entity neighborhood traversal root_influence_map(project) Who touched this project, through what root_decision_trail(topic) How decisions evolved over time root_blind_spots() Entities with declining activity root_ask(question) Free-form Q&A (GraphRAG) root_weekly_digest() Weekly activity summary ``` --- ## Use Cases ### For Product Managers - **"Who influences Project X?"** `root_influence_map("Project X")` shows every stakeholder, their role, and evidence from meetings and notes - **"What decisions were made about pricing?"** `root_decision_trail("pricing")` traces the chronological evolution - **"What did I promise Ric last week?"** `root_open_loops("Ric")` surfaces unfollowed action items - **"Brief me before my 1:1"** `root_about("colleague name")` pulls everything across all sources ### For Engineers - **"How does the auth system work?"** `root_ask("authentication architecture")` synthesizes from architecture docs, meeting notes, and ADRs - **"What depends on this service?"** `root_graph("service name", 2)` shows the dependency graph - **"What's gone stale?"** `root_blind_spots()` finds topics that were hot but went silent ### For Researchers & Writers - **"What themes connect my notes?"** `root_themes()` discovers patterns via clustering - **"What am I missing about this topic?"** `root_gaps("your topic")` finds blind spots - **"Connect the dots"** `root_connections("note path")` finds unexpected cross-domain links ### For Teams - **"Weekly knowledge pulse"** `root_weekly_digest()` summarizes what changed across all sources - **"Project health check"** `root_project_pulse("project")` shows activity across notes, meetings, and email --- ## LLM Backends Three backends for entity extraction and Q&A synthesis: | Backend | Cost | Quality | Setup | |---------|------|---------|-------| | **Anthropic** (default) | ~$3-5 per 2,500 notes | Best | `ANTHROPIC_API_KEY` in `.env` | | **OpenRouter** | Free $1 credit to start | Good | `OPENROUTER_API_KEY` in `.env` | | **Ollama** | Free (runs locally) | Lower | `ollama pull llama3.1` | Set in `config.yaml`: ```yaml llm: backend: "anthropic" # or "openrouter" or "ollama" ``` --- ## Auto-Refresh ROOT supports automatic re-indexing so your knowledge graph stays fresh. ### macOS (recommended: cron) Cron is recommended over launchd because macOS TCC restrictions prevent launchd agents from accessing `~/Documents` and iCloud paths. ```bash # Add to crontab (runs every 2 hours at :30) crontab -e # Add this line: 30 8,10,12,14,16,18,20,22 * * * ANTHROPIC_API_KEY=your-key-here /path/to/root-kg/.venv/bin/python /path/to/root-kg/indexer.py --extract >> ~/Library/Logs/root-indexer.log 2>> ~/Library/Logs/root-indexer.err ``` Only changed notes are reprocessed. Typical incremental run: Built by Shadman Rahman ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [mshadmanrahman](https://github.com/mshadmanrahman) - **Source:** [mshadmanrahman/root-kg](https://github.com/mshadmanrahman/root-kg) - **License:** MIT - **Homepage:** https://github.com/mshadmanrahman/root-kg 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-mshadmanrahman-root-kg - Seller: https://agentstack.voostack.com/s/mshadmanrahman - 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%.