Gentic Knowledge — Documentation
Everything you need to give your AI agent a knowledge base — ingest documents, web pages, and text, then search semantically.
1. Getting Started
Sign Up & Get Your API Key
Before you can use Gentic Knowledge, you need an API key to authenticate your requests.
- Go to gentic.co/knowledge and create an account.
- Create an organization from your dashboard. API keys, billing, and knowledge base data are all scoped to the organization.
- Go to the API Keys section in your dashboard.
- Click Create API Key. Give it a name (e.g. "Claude Code" or "n8n production").
- Copy the key immediately — it starts with
gentic_and is only shown once.
Anyone on your team can generate their own key, and they'll all share the same knowledge base.
Keep your key secure. Treat it like a password. Don't commit it to version control or share it publicly.
2. Connecting to the MCP Server
Gentic Knowledge uses the Model Context Protocol (MCP) — an open standard for connecting AI agents to external tools. You connect once, and your agent gets access to all Gentic Knowledge tools automatically.
Server URL: https://mcp.gentic.co/knowledge
Claude Code (CLI)
Option A — OAuth (no API key needed):
claude mcp add gentic-knowledge --transport http https://mcp.gentic.co/knowledgeOption B — API key:
claude mcp add gentic-knowledge \
--transport http \
https://mcp.gentic.co/knowledge \
--header "Authorization: Bearer YOUR_API_KEY"Claude Web / ChatGPT
Add as a connector in your settings. Enter the server URL and authenticate via OAuth — no API key needed.
Server URL: https://mcp.gentic.co/knowledgen8n
Add an MCP node with this configuration:
{
"name": "gentic-knowledge",
"type": "mcp",
"config": {
"url": "https://mcp.gentic.co/knowledge",
"transport": "streamable-http",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}OpenClaw / Other MCP Clients
Add to your MCP config:
{
"mcpServers": {
"gentic-knowledge": {
"url": "https://mcp.gentic.co/knowledge",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}Any Other MCP Client
Gentic Knowledge uses standard Streamable HTTP transport. Any client that supports MCP can connect using the server URL and either OAuth or API key Bearer token authentication.
Agent Skills (Recommended)
For the best results, pair the MCP server with the Gentic agent skill. The MCP server gives your agent access to the tools; the skill teaches it the optimal workflow order — ingesting content, searching the knowledge base, and managing sources.
1. Add the MCP server (if you haven't already):
claude mcp add gentic-knowledge --transport http https://mcp.gentic.co/knowledge --header "Authorization: Bearer <your-api-key>"2. Install the agent skill:
npx skills add gentic-co/agent-skillsOr add the skill directly via URL:
https://gentic.co/knowledge/SKILL.md- MCP server — provides tool access (vectorize, search, delete, list sources)
- Agent skill — teaches the optimal workflow order: index content → search knowledge → manage sources
Works with Claude Code, Cursor, Copilot, and 40+ other agents.
3. Vectorize Documents
Use vectorize_document to ingest document files into your knowledge base. Supported formats: PDF, DOCX, TXT, RTF.
Accepts any HTTP URL or Google Drive sharing link. The document is processed asynchronously — content is extracted, chunked into ~1,000 character segments, embedded using Gemini, and stored in your organization's knowledge base.
Parameters
| Parameter | Required | Description |
|---|---|---|
| file_url | Yes | HTTP URL or Google Drive link to the document |
| title | No | Human-readable title for the document |
| category | No | Category tag for filtering (e.g. "brand-guidelines", "campaign-briefs") |
Example
"Vectorize this PDF of our brand guidelines: https://example.com/brand-guide.pdf"
Processing is asynchronous. Your agent will receive a job ID and can check the status. Once complete, the content is immediately searchable.
Cost: $0.05 per chunk (~1,000 characters each).
4. Vectorize Text Content
Use vectorize_content to ingest raw text — emails, Slack messages, reviews, social posts, creator feedback, or notes.
Parameters
| Parameter | Required | Description |
|---|---|---|
| content | Yes | The text content to vectorize |
| title | Yes | Title for the content piece |
| source_type | No | One of: email, slack, review, social, creator_feedback, note, other |
| category | No | Category tag for filtering |
Example
"Save this customer review to our knowledge base: [paste review text]"
Content is chunked, embedded, and indexed. For short text (under 1,000 characters), it becomes a single chunk.
Cost: $0.05 per chunk.
5. Vectorize Web Pages
Use vectorize_web_content to scrape a web page, extract clean text, chunk, and embed it.
Parameters
| Parameter | Required | Description |
|---|---|---|
| url | Yes | URL of the web page to scrape |
| title | No | Title for the content (auto-detected if omitted) |
| category | No | Category tag for filtering |
Example
"Index our FAQ page: https://example.com/faq"
The page is scraped, HTML is stripped, and clean text is chunked and embedded.
Cost: $0.05 per chunk + $0.05 scraping fee.
6. Search Knowledge
Use search_knowledge to semantically search across all indexed content. Your query is embedded and matched against stored chunks using cosine similarity.
Parameters
| Parameter | Required | Description |
|---|---|---|
| query | Yes | Natural language search query |
| source_types | No | Filter by source types (e.g. ["email", "slack"]) |
| category | No | Filter by category |
| document_id | No | Search within a specific document |
| limit | No | Max results (default 10, max 50) |
Example
"Search our knowledge base for our refund policy"
Results include the matching text chunk, similarity score, source document title, source type, and metadata. Results are ranked by relevance.
Cost: Free.
7. Manage Sources
List Sources
Use list_kb_sources to see everything in your knowledge base — document titles, source types, chunk counts, categories, and creation dates.
"Show me everything in our knowledge base"
Delete Content
Use delete_content to remove content from your knowledge base. You can delete by document ID (removes all chunks) or by specific chunk IDs.
| Parameter | Required | Description |
|---|---|---|
| document_id | No* | Delete all chunks for a document |
| content_ids | No* | Delete specific chunks by ID |
* At least one of document_id or content_ids is required.
Deletion is a soft delete — content is excluded from search results but retained in the database.
8. Tool Reference
Complete reference for all 6 knowledge tools available via the MCP server at mcp.gentic.co/knowledge.
| Tool | Purpose | Cost |
|---|---|---|
| vectorize_document | Ingest PDF, DOCX, TXT, or RTF files | $0.05/chunk |
| vectorize_content | Ingest raw text (emails, Slack, reviews, notes) | $0.05/chunk |
| vectorize_web_content | Scrape and ingest web pages | $0.05/chunk + $0.05 |
| search_knowledge | Semantic search across all content | Free |
| list_kb_sources | List all indexed documents and sources | Free |
| delete_content | Soft-delete content by document or chunk | Free |
9. Pricing
Gentic Knowledge uses pay-per-chunk pricing. Each chunk is approximately 1,000 characters.
| Action | Cost |
|---|---|
| Vectorize document chunk | $0.05 |
| Vectorize text content chunk | $0.05 |
| Web scraping fee | $0.05 |
| Search knowledge | Free |
| List sources | Free |
| Delete content | Free |
Example cost
A 10-page PDF produces roughly 30 chunks = $1.50. A short email or Slack message is typically 1 chunk = $0.05. Once indexed, every search query is free — no matter how many times your agent searches.
No subscriptions. No storage fees. No seat licenses. You only pay when you ingest new content.