Integration
Connect PostgreSQL to Azure AI Search Vector Store
When New or Updated Row fires in PostgreSQL, your agent runs Upload Documents in Azure AI Search 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 PostgreSQL and Azure AI Search Vector Store to do together?
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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 PostgreSQL can start in Azure AI Search Vector Store
When New or Updated Row in PostgreSQL
then Upload Documents in Azure AI Search 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 PostgreSQL and Azure AI Search Vector Store
Triggers and actions 4 triggers · 13 actions
- New or Updated Row
Triggers when a new row is added or modified.
- New or Updated Row (Custom Query)
Fires for each new or changed row returned by a SELECT statement you write against the connected PostgreSQL database.
- New Row
Triggers when you add a new row.
- New Table
Fires when a new table appears in the connected PostgreSQL database.
- Add Row
Adds a new row.
- Delete Row
Delete the rows in a table whose chosen column equals a value.
- Find Row
Finds a row in a table via a lookup column.
- Find Rows via Custom Query
Runs a SELECT statement you write against the connected PostgreSQL database and returns every row it matches.
- Find Row via Custom Query
Runs a SELECT statement you write against the connected PostgreSQL database and returns the first row it matches.
- Update Row
Updates an existing row.
- Create Index
Creates a search index with the fields you define, including vector fields for similarity search.
- Delete Index
Deletes a search index and every document in it.
- Get Document
Returns one document from a search index by its key.
- Get Index
Returns a search index's definition: its fields, vector search and semantic settings.
- List Indexes
Returns the search indexes in your Azure AI Search service.
- Search Documents
Searches a search index by keywords, filter and/or vector similarity and returns the matching documents with their scores.
- Upload Documents
Adds documents to a search index, replacing any existing document with the same key.
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
PostgreSQL and Azure AI Search Vector Store, answered
What can start an automation from PostgreSQL?
Any of PostgreSQL's 4 triggers in the catalog, including New or Updated Row, New or Updated Row (Custom Query), New Row and New Table. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Azure AI Search Vector Store when something happens in PostgreSQL?
Any of Azure AI Search Vector Store's 7 actions, including Create Index, Upload Documents, Get Document and Get Index. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Azure AI Search Vector Store to PostgreSQL?
Azure AI Search Vector Store has no triggers in the catalog today, so automations start in PostgreSQL. If you need the other direction, ask: your agent reads Azure AI Search Vector Store's API documentation and adds it.
Do I have to build a connector for PostgreSQL or Azure AI Search 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 PostgreSQL and Azure AI Search 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.