Integration
Connect PandaDoc to Qdrant Vector Store
When Document completed fires in PandaDoc, your agent runs Add collection in Qdrant Vector Store. Describe the whole flow and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want PandaDoc and Qdrant Vector Store to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiOne connection does both: ask your client to act in an app once, or have it build an automation that keeps running. Any client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.
Set it up in your client
Claude Code
Run this in the directory you want to work in.
claude mcp add --transport http -s project apiant-ai https://mcp.apiant.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)Claude, web and desktop
Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.
Setup guide (opens in a new tab)Cursor
Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.
Setup guide (opens in a new tab)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)Codex and the ChatGPT desktop app
Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.
Setup guide (opens in a new tab)Any other MCP client
Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.
Setup guide (opens in a new tab)Example flows
What PandaDoc can start in Qdrant Vector Store
When Document completed in PandaDoc
then Add collection in Qdrant Vector Store
Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.
Everything your agent can do with PandaDoc and Qdrant Vector Store
Triggers and actions 3 triggers · 34 actions
- Document completed
Polling trigger. Fires when a document reaches completed status. Dedup by document id.
- Document completed (instant)
Instant trigger: fires when a PandaDoc document reaches the completed state. Self-registering — APIANT creates the PandaDoc webhook when you turn the automation on and removes it when you turn it off, so there is nothing to paste. Only document_state_changed events with status document.completed are passed through; each fires once with the document id, name, status, created/modified/completed timestamps and the full document object.
- Document updated
Polling trigger. Fires when a document is created or changes status. Dedup by document id + date_modified.
- Change document status
Manually changes a document's status (e.g. to mark paid or voided). Only certain transitions are allowed.
- Create contact
Creates a new contact.
- Create document from template
Creates a new document from a template, with recipients, tokens, fields, and pricing tables.
- Create document link
Generates a shareable session link for a recipient to view/sign a document.
- Delete contact
Deletes a contact by ID.
- Delete document
Deletes a document by ID.
- Download document PDF
Returns the document as a PDF file. Use watermark options as needed.
- Find document by name
Finds a document by name and emits its ID. An error occurs if none or more than one is found.
- Get document details
Retrieves detailed data for a single document by ID, including recipients, tokens, fields, and metadata.
- Get document entered data
Emits arrays of field and token names and values for the specified document.
- Get document status
Returns the current status of a document by ID.
- Get template details
Retrieves details for a template by ID, including roles, fields, tokens, and pricing tables.
- List contacts
Lists contacts in the workspace.
- List documents
Lists documents, optionally filtered by status, template, folder, or search query.
- List folders
Lists document folders.
- List members
Lists workspace members (users).
- List templates
Lists available document templates.
- Send document
Moves a draft document to sent status, optionally emailing recipients with a subject and message. Set silent to suppress notifications.
- Update contact
Updates an existing contact by ID.
- Add collection
Creates a new Qdrant collection with the vector size, distance metric and storage settings you choose.
- Add payload index
Creates a payload index on a field of a Qdrant collection so filters and searches on that field run faster.
- Add points
Adds points (vectors with optional payloads) to a Qdrant collection, overwriting any existing points that have the same ids.
- Add snapshot
Creates a new snapshot of a Qdrant collection and returns the snapshot's name, size, checksum and creation time.
- Count points
Returns how many points in a Qdrant collection match an optional filter, or the total number of points when no filter is given.
- Delete collection
Deletes a collection and all of the points and data stored in it.
- Delete points
Deletes points from a Qdrant collection, either by a list of point ids or by every point matching a filter.
- Find points by vector
Returns the points in a collection whose vectors are nearest to the vector you supply, ranked by similarity score, with their payloads.
- Get collection
Returns the details of a collection: its status, point and segment counts, vector and index configuration, and payload schema.
- Get point
Returns a single point from a Qdrant collection by its id, including its payload and vector.
- List collections
Returns the names of every collection in your Qdrant instance.
- List points
Returns the points stored in a Qdrant collection, optionally narrowed by a filter and ordered by a payload field, fetching every page.
- List snapshots
Returns every snapshot taken of a collection, with each snapshot's name, size, checksum and creation time.
- Update collection
Updates the settings of an existing Qdrant collection, such as its vector, index, optimizer, quantization, strict-mode or metadata parameters.
- Update point payload
Sets payload values on the chosen points in a Qdrant collection, merging them into each point's existing payload. Pick the points by id or by a filter.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
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Questions
PandaDoc and Qdrant Vector Store, answered
What can start an automation from PandaDoc?
Any of PandaDoc's 3 triggers in the catalog, including Document completed, Document completed (instant) and Document updated. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Qdrant Vector Store when something happens in PandaDoc?
Any of Qdrant Vector Store's 15 actions, including Update collection, Update point payload, Add collection and Add payload index. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Qdrant Vector Store to PandaDoc?
Qdrant Vector Store has no triggers in the catalog today, so automations start in PandaDoc. If you need the other direction, ask: your agent reads Qdrant Vector Store's API documentation and adds it.
Do I have to build a connector for PandaDoc or Qdrant Vector Store?
No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.
Can my AI client use PandaDoc and Qdrant Vector Store without building an automation?
Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both.
What happens when something fails?
Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.
Is there a free plan?
Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.