Note-Taking & Knowledge Base
Build a smart knowledge base in Notion with auto-organization, web research, and intelligent retrieval
🧂 Ingredients
🔌 APIs
database_for_storing_organizing_and_querying_notes_and_knowledge
🔄 Alternatives:
web_research_to_enrich_notes_with_additional_context
🔄 Alternatives:
extract_content_from_urls_to_save_as_notes
🔄 Alternatives:
📋 Step-by-Step Build Guide
Create a Notion database with properties
1. Create a Notion database with properties: Title, Tags (multi-select), Category, Source URL, Date Added, Summary, Related Notes
Interact with the Notion database using the Notion API.
POST https://api.notion.com/v1/pages (to create)
POST https://api.notion.com/v1/databases/{db_id}/query (to query)
Headers: Authorization: Bearer {NOTION_TOKEN}, Notion-Version: 2022-06-28, Content-Type: application/json
For creating pages: structure properties to match the database schema.
For querying: use filters and sorts to get relevant entries.
Handle rich text by wrapping content in the proper block format.
If the API returns 429 (rate limited), wait 1 second and retry. Max 3 retries.Build a 'capture' command
2. Build a 'capture' command — when you send a URL, the agent fetches the content, summarizes it, and saves to Notion
Interact with the Notion database using the Notion API.
POST https://api.notion.com/v1/pages (to create)
POST https://api.notion.com/v1/databases/{db_id}/query (to query)
Headers: Authorization: Bearer {NOTION_TOKEN}, Notion-Version: 2022-06-28, Content-Type: application/json
For creating pages: structure properties to match the database schema.
For querying: use filters and sorts to get relevant entries.
Handle rich text by wrapping content in the proper block format.
If the API returns 429 (rate limited), wait 1 second and retry. Max 3 retries.Build a 'note' command
3. Build a 'note' command — quickly capture a thought with auto-tagging based on content analysis
Build a 'note' command — quickly capture a thought with auto-tagging based on content analysis Steps: 1. Validate all required inputs are available 2. Execute the operation described above 3. Verify the result meets expected output format 4. Handle errors gracefully — retry transient failures, log and alert on persistent ones 5. Return structured output with status and any relevant data If any required data is missing, request it from the user before proceeding.
Auto
4. Auto-organization: periodically scan new notes and suggest/apply tags based on content
Auto-organization: periodically scan new notes and suggest/apply tags based on content Steps: 1. Validate all required inputs are available 2. Execute the operation described above 3. Verify the result meets expected output format 4. Handle errors gracefully — retry transient failures, log and alert on persistent ones 5. Return structured output with status and any relevant data If any required data is missing, request it from the user before proceeding.
When adding a note on a topic, search existing notes for related entries and lin
5. When adding a note on a topic, search existing notes for related entries and link them
When adding a note on a topic, search existing notes for related entries and link them Steps: 1. Validate all required inputs are available 2. Execute the operation described above 3. Verify the result meets expected output format 4. Handle errors gracefully — retry transient failures, log and alert on persistent ones 5. Return structured output with status and any relevant data If any required data is missing, request it from the user before proceeding.
Enrich notes with web search
6. Enrich notes with web search — add relevant context, statistics, or related resources
Enrich notes with web search — add relevant context, statistics, or related resources Steps: 1. Validate all required inputs are available 2. Execute the operation described above 3. Verify the result meets expected output format 4. Handle errors gracefully — retry transient failures, log and alert on persistent ones 5. Return structured output with status and any relevant data If any required data is missing, request it from the user before proceeding.
Natural language search
7. Natural language search: 'What do I know about X?' queries your Notion DB and returns relevant notes
Interact with the Notion database using the Notion API.
POST https://api.notion.com/v1/pages (to create)
POST https://api.notion.com/v1/databases/{db_id}/query (to query)
Headers: Authorization: Bearer {NOTION_TOKEN}, Notion-Version: 2022-06-28, Content-Type: application/json
For creating pages: structure properties to match the database schema.
For querying: use filters and sorts to get relevant entries.
Handle rich text by wrapping content in the proper block format.
If the API returns 429 (rate limited), wait 1 second and retry. Max 3 retries.Weekly
8. Weekly: generate a 'knowledge digest' — new notes added, connections discovered, gaps in your knowledge
Weekly: generate a 'knowledge digest' — new notes added, connections discovered, gaps in your knowledge Steps: 1. Validate all required inputs are available 2. Execute the operation described above 3. Verify the result meets expected output format 4. Handle errors gracefully — retry transient failures, log and alert on persistent ones 5. Return structured output with status and any relevant data If any required data is missing, request it from the user before proceeding.
🤖 Example Agent Prompt
Interact with the Notion database using the Notion API.
POST https://api.notion.com/v1/pages (to create)
POST https://api.notion.com/v1/databases/{db_id}/query (to query)
Headers: Authorization: Bearer {NOTION_TOKEN}, Notion-Version: 2022-06-28, Content-Type: application/json
For creating pages: structure properties to match the database schema.
For querying: use filters and sorts to get relevant entries.
Handle rich text by wrapping content in the proper block format.
If the API returns 429 (rate limited), wait 1 second and retry. Max 3 retries.Copy this prompt into your agent to get started.