Knowledge Raven
Knowledge Raven is not a competitor to Confluence, Notion, or GitHub MCPs — those are data sources. Knowledge Raven is the aggregation layer that connects all your tools and makes their knowledge searchable through one unified interface for any AI agent.
Connect your company’s knowledge sources once. Any AI agent — Claude, ChatGPT, Gemini, Cursor — instantly searches everything via the Model Context Protocol (MCP).
What is Knowledge Raven?
Knowledge Raven is a SaaS platform that centrally stores and indexes your company knowledge, making it accessible to AI agents through a standard MCP interface. Instead of building separate integrations for each knowledge source, you connect once to Knowledge Raven and your agents can search everything.
How it works:
- Connect your knowledge sources: Confluence spaces, Notion pages, GitHub repositories, Dropbox folders, Google Drive
- Knowledge Raven indexes all content automatically — text extraction, chunking, embedding, and hybrid search are fully handled for you
- Your AI agent searches through all connected knowledge using 6 MCP tools with intelligent query routing
No embedding knowledge required. No vector database to manage. No pipelines to maintain.
Key Differentiator: Agentic RAG with 3 Query Types
Most knowledge tools offer basic vector search. Knowledge Raven uses Agentic RAG — the agent dynamically selects the optimal retrieval strategy per query:
| Query Type | Strategy | When Used |
|---|---|---|
| Precision | Vector-heavy (70% semantic + 30% BM25) | Specific questions with known keywords |
| Explorative | BM25-heavy (30% semantic + 70% keyword) | Broad topic exploration |
| Discovery | Metadata-only | Browsing available documents without search |
This means your agent finds relevant knowledge even when queries are vague, exploratory, or cross-document — not just when they contain exact keyword matches.
MCP Tools
6 tools give your agent full control over retrieval:
search_knowledge_base— Precision search within a specific knowledge basebroad_search— Explorative search across all knowledge basesfetch_document— Retrieve a specific document (preview, full, or by chunks)list_knowledge_bases— Discover available knowledge baseslist_documents— Browse documents with summariesget_document_metadata— Retrieve metadata without loading full content
Connectors
| Connector | Status |
|---|---|
| Confluence | Live |
| Notion | Live |
| GitHub | Live |
| Dropbox | Live |
| Google Drive | OAuth verification pending |
Pricing
| Plan | Documents | Users | Queries | Price |
|---|---|---|---|---|
| Free | 50 | 3 | 100 / user / month | $0 |
| Pro | 500 | 15 | Unlimited | $29 / workspace / month |
| Enterprise | Unlimited | Unlimited | Unlimited | Custom |
All plans include all connectors and all 6 MCP tools. Upgrade anytime from your workspace settings.
Supported Formats
Knowledge Raven uses Gemini Embedding 2 — a natively multimodal embedding model. Supported content types:
- Text: PDF, DOCX, TXT, Markdown, CSV
- Images: PNG, JPEG (via multimodal embedding — no separate OCR pipeline)
- Audio: MP3, WAV, M4A (via multimodal embedding)
- Video: MP4, MOV up to 120 seconds (via multimodal embedding)
Quick Start
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