ChatGPT Plugin

Heptabase

Search and update your notes

Brand: Heptabase

Category: Productivity
Primary Subcategory: Notes & Personal Knowledge Bases

Integration details

Description

Connect ChatGPT to your Heptabase knowledge base. Search and read cards, journals, PDFs, tags, databases, and whiteboards; view selected cards in an interactive reader; create and edit notes; update properties; and place existing objects on whiteboards.

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: Productivity
Primary Subcategory: Notes & Personal Knowledge Bases
Secondary Subcategories: None listed
Brand: Heptabase
Access: Account required
First tracked: 2026-09-01
Tool count: 21
Geography: US

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Primary Subcategory

Competing in ChatGPT Notes & Personal Knowledge Bases

View Category

Listed in alphabetical order

Primary Subcategory

Agent KBComing soonGet notified

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Tools

21 tools agents can invoke

Add up to 200 cards to an existing Heptabase tag database. Use list_tags or read_database to get the database ID or tag ID. Use card listing, search, read, or create results to get card IDs. Repeated additions are skipped. Remove is not yet supported.
update_database_card_membership
Append content to a journal in Heptabase. If the journal for the specified date does not exist, it will be created. IMPORTANT: Pass the `date` parameter with the user's current local date (YYYY-MM-DD) to avoid timezone mismatch.
append_to_journal
Create a new note card or fill a missing or empty daily journal in the user's Heptabase space. Existing journal content is never overwritten. Write content in Hepta Markdown.
create_object
Edit property values on cards that already belong to a Heptabase tag database. Use read_database first to get the database identifiers, property IDs and types, select options, and relation target database IDs. Edits are evaluated independently and in input order. Use null to clear a property.
edit_card_properties
Replace exact content in a note card or journal. Read the object first, remove only line-number prefixes, and use the shortest unique oldString. The tool preserves supported formatting and returns an excerpt of the applied edit when available.
edit_object_content
Get a temporary download URL for an original file stored in Heptabase. Pass a fileId from a read, list, or search result and its containing source object. Download the bytes yourself using HTTP; this tool does not return file contents. Supports uploaded PDFs, videos, audio, images, and attachments. Request a new URL when it expires.
get_file_download_url
List cards by type, whiteboard or tag membership, timestamps, or known IDs without reading their content. When more cards match than the current page, the result includes the total matching count.
list_cards
List all tags in the user's Heptabase knowledge base with card counts and hierarchy. USE WHEN: - You need to discover what tags exist before drilling into a specific tag - User asks "what are my tags?" or "how is my knowledge organized?" - You want to find the right tag ID before calling list_cards RETURNS: - All tags grouped by tag group (if any) - Card count per tag - Parent-child tag hierarchy - Tag IDs for use with list_cards or read_database STRATEGY: - Call this first to discover tags, then use list_cards with tagIds to list a specific tag's cards - Use read_database when you need a tag database's property schema or views - Use the optional nameFilter to narrow results if the user mentions a topic
list_tags
List the user's whiteboard hierarchy with lightweight object counts and pagination.
list_whiteboards
Automatically place up to 100 existing objects on a whiteboard. Split larger batches across calls. Accepted objectType values are card, journal, pdfCard, imageCard, videoCard, audioCard, and webCard. The batch is packed left-to-right immediately to the right of persisted content, and every valid item creates a new instance even when it is already present. This auto-only phase does not infer Section membership or adjust Sections, neighboring objects, connections, or lint. Retrying may create duplicates.
place_whiteboard_objects
Read Heptabase reference documentation. `concepts` explains cards, whiteboards, and tag databases. `hepta_markdown` defines the rich-text syntax for tables, object mentions, and text or background colors used by `create_object`, `append_to_journal`, and `edit_object_content`. `properties` documents database property types and editable values. Omit `path` to list all three pages.
read_system_manual_page
Read specific pages from a parsed PDF card in the user's Heptabase knowledge base. Page numbers are 1-indexed and inclusive.
read_pdf
Read a tag database configuration by database ID, tag ID, or both, including its property schema, views, filters, sorts, select options, and relation targets.
read_database
Read a whiteboard's structure or object content from the user's Heptabase knowledge base. Use structure mode to inspect its organization, or content mode to read and analyze the objects on it.
read_whiteboard
Read an image referenced by read_object. Pass the file and source object fields from the image reference.
read_image
Read a specific object from the user's Heptabase knowledge base. Use this after another tool returns an object ID. Text content uses 1-based absolute line numbers for reference; the number prefixes are not part of the content. Use offset and limit to continue reading long content. For a PDF card, this returns metadata; use read_pdf to read its pages.
read_object
Read existing daily journal entries within an inclusive date range from the user's Heptabase knowledge base, oldest first. USE WHEN: - User asks about their journal entries during a time period - User wants to see what they wrote in past days, weeks, or months - User needs to review their daily notes IMPORTANT CONSTRAINTS: - Each call can retrieve at most 92 days (approximately 3 months) - For longer periods, make multiple calls - Dates use YYYY-MM-DD format. Both startDate and endDate are inclusive.
read_journal_range
Search the user's entire main Heptabase Space by exact keywords or short phrases. It searches titles and supported text content, while PDFs, video cards, and audio cards are title-only. Results include concise object summaries and matching excerpts; use read_object or read_pdf for complete content.
search_by_keyword
Search the user's Heptabase space semantically using a natural-language query. Use this for ideas, concepts, or meanings that exact keywords may miss. Results contain concise object summaries and excerpts; use read_object or read_pdf when complete content is needed. This does not search tags or whiteboards.
search_by_semantic
Search literal or regex text inside one known object in the user's Heptabase knowledge base. Returns excerpts with absolute 1-based line numbers, marks matching lines with `*`, and searches stored parsed page content for PDF cards. Use another search tool or read_object first to obtain the object ID and type.
search_object_content
Present selected Heptabase cards in an interactive UI. After searching, recommending, creating, or editing cards, render the card or small set selected for the user before answering. Complete requested changes first. Use in clients that support MCP Apps; in plain-text/CLI clients, respond in text instead. Supports notes, journals, PDF, video, audio, image, web cards, and highlights.
render_cards

FAQs

Heptabase ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

Read the methodology

How do I improve Heptabase's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

What are Heptabase alternatives on ChatGPT?

As of 2026-10-16, Heptabase competes with Agent KB, Atlavium, AudioPen, beckett, Capacities, Clariia AI Inbox, ClippingMini, Craft and 35 more in ChatGPT Notes & Personal Knowledge Bases, ranked by public Discoverability Score.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.