Gentic Knowledge — Documentation

1. Getting Started

Sign Up & Get Your API Key

Before you can use Gentic Knowledge, you need an API key to authenticate your requests.

1. Go to gentic.co/knowledge and create an account.
2. Create an organization from your dashboard. API keys and billing are scoped to the organization.
3. Generate an API key and use it as a Bearer token in your MCP client.

2. Connecting to the MCP Server

The server is available at https://mcp.gentic.co/knowledge. For Claude Code:

claude mcp add gentic-knowledge \
  --transport http \
  https://mcp.gentic.co/knowledge \
  --header "Authorization: Bearer YOUR_API_KEY"

For Claude Web and ChatGPT you can also connect via OAuth — no API key needed. See the connect section on the landing page for other MCP clients (n8n, OpenClaw).

3. Agent Skill

For the best results, pair the MCP server with the Gentic Knowledge agent skill. The MCP server gives your agent tool access; the skill teaches it the optimal workflow order. Both the raw SKILL.md and a ready-to-upload .skill bundle are generated on demand from the live manifest, so they always reflect the current tools and pricing.

Add the skill directly via URL:

https://gentic.co/knowledge/SKILL.md

Or upload a .skill bundle to Claude Managed Agents:

https://gentic.co/knowledge/gentic-knowledge.skill

Download this file and upload it wherever Claude Managed Agents asks for a .skill file. It's a zip bundle generated on demand from the latest SKILL.md.

4. When to Apply

• User wants to add documents, web pages, or text content to a knowledge base.
• User wants to search a knowledge base semantically rather than by keyword.
• User wants to see what content has been indexed, or delete content from their knowledge base.
• User mentions "knowledge base", "vectorize", "index", "semantic search", or "RAG".
• User wants to store and search emails, Slack messages, reviews, notes, or other unstructured text.

5. Workflow

1. 1. Pick the right ingestion tool

   Three tools, one chooser: **`vectorize_document`** for PDF/TXT/RTF/DOCX files (accepts HTTPS and Google Drive URLs), **`vectorize_web_content`** for live web pages (auto-scraped, cleaned, chunked; thin pages retried with JS rendering), **`vectorize_content`** for raw text (emails, Slack, reviews, notes — requires `source_type` of `email`/`slack`/`review`/`social`/`creator_feedback`/`note`/`other`). For the text tool, pass a `source_id` (e.g. email thread ID) to deduplicate. All three accept optional `title` and `category`.

2. 2. Ingestion is async — tell the user

   All vectorize tools run in the background. Content becomes searchable in ~10–60 seconds depending on size. **Don't block waiting.** Tell the user it's processing and call `list_kb_sources` afterwards to confirm indexing finished. Don't run `search_knowledge` immediately after ingestion and claim "no results" — the embeddings aren't ready yet.

3. 3. Surface ingestion cost before large uploads

   A chunk is ~1,000 characters at **5¢/chunk**. A short email is 1 chunk. A 10-page document is ~20–40 chunks. A 50-page PDF is ~150 chunks ≈ **$7.50**. `vectorize_web_content` additionally charges a **5¢ scraping fee** on top of the per-chunk cost. **Surface an estimate before the user indexes large documents or bulk content** — "this PDF will likely produce ~X chunks at 5¢ each ≈ $Y".

4. 4. Search is free — use it aggressively

   `search_knowledge` costs nothing, so encourage the user to refine queries. Key params: `query` (natural language, be descriptive), `source_types` filter (e.g. `["document", "web"]` or `["email", "slack"]`), `category` filter, `document_id` to scope to one source, `limit` (default 10, max 50). Results come ranked by similarity score.

5. 5. Present results with source context

   Show the most relevant snippets with their source info (title, type, category) and similarity scores. When searching across many sources, **group by document or source type**. Mention the total result count. If scores are all low, offer to broaden the search or check `list_kb_sources` to confirm the relevant content is actually indexed.

6. 6. Manage sources cleanly

   `list_kb_sources` shows everything indexed — title, source type, chunk count, category, date. Use it to verify ingestion completed or find `document_id` values for deletion. `delete_content` is a **soft delete** — removes chunks from search but retains them in storage. Delete by `document_id` to remove all chunks for a source, or by `content_ids` to remove specific chunks.

7. 7. Encourage categories on ingest

   The `category` field is the single best thing the user can set for future search ergonomics — it lets them filter search to a subset later (e.g. `category="support"` vs `"legal"`). Always offer a category suggestion on ingest instead of leaving it blank.

6. Tool Reference

6 tools, rendered live from the Gentic MCP manifest. Parameter tables come directly from each tool's JSON Schema.

7. Pricing

Pricing is pulled live from the Gentic MCP manifest. All prices are per call and deducted from your Gentic credits.

8. Notes

• All tools are organization-scoped — users only see their own knowledge base.
• Ingestion is **async**. Content takes ~10–60s to become searchable. Don't run `search_knowledge` immediately and claim it's missing.
• Ingestion costs are **5¢/chunk** (~1,000 chars each). `vectorize_web_content` adds a **5¢ scraping fee**. Search is free.
• Content is deduplicated by document ID / `source_id`. Re-vectorizing the same URL or source_id updates rather than duplicates.
• `delete_content` is soft-delete — chunks are excluded from search but retained in storage.