hermes

Connect Hermes to Qdrant

Give an AI agent your Qdrant instance as a tool and it can manage its own search index and long-term memory while it works. It can create a collection, upsert points, run a vector query or a recommendation, retrieve or scroll matching records, and set or clear payload metadata on its own, calling each operation as a tool. That turns retrieval from a fixed pipeline into something the agent drives directly, storing what it learns and searching it back when it needs context.

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Opens a workflow with 18 tools ready to use.

Tools Hermes gets

Pick the operations you want and each becomes a tool the agent can call directly while it works.

Qdrant

18 tools
Query / Search

Find the most similar points to a query vector (similarity search).

Upsert Points

Insert or overwrite points in a collection.

Retrieve Points

Retrieve points by their IDs.

Delete Points

Delete points by ID or by filter.

Scroll Points

Scroll through all points in a collection with optional filter and cursor-based pagination.

Count Points

Count points in a collection, with optional filter.

Recommend Points

Find points similar to positive examples and dissimilar from negative examples.

List Collections

List all collections.

Get Collection Info

Get detailed info and stats for a single collection.

Create Collection

Create a new collection.

Update Collection

Update collection parameters (optimizers, HNSW, quantization).

Delete Collection

Delete a collection and all its points permanently.

Set Payload

Set (merge) payload fields on points selected by IDs or filter.

Delete Payload Keys

Delete specific payload keys from points.

Clear Payload

Remove all payload from points selected by IDs or filter.

Create Payload Index

Create a payload field index to speed up filtered searches.

Delete Payload Index

Delete a payload field index.

Upload & Index Document

Upload a document file, chunk + embed it, and upsert the points.

What you can build

When a new document lands in your pipeline, embed it and call Upload and Index Document to add it to a Qdrant collection automatically.
On each incoming support ticket, run a Query / Search against your knowledge base collection and return the closest matching articles.
Every night, use Scroll Points to page through a collection and Delete Points for records that are past their retention window.
When a product is updated, upsert its new embedding with Upsert Points and refresh its metadata with Set Payload in the same run.
Feed a customer's recent purchases into Recommend Points to surface similar items for a personalized follow-up email.
Before a bulk import, call Create Collection with the right vector size and add a Create Payload Index so filtered searches stay fast.

About Hermes

Hermes is an open agent built on Nous Research’s Hermes models. NoClick runs it hosted and connects your apps to it as tools, so it can do real work across your systems. Wire an integration into the agent and Hermes can use that app’s operations directly while it reasons through a task. It is a strong pick when you want an open-model agent with genuine tool access.

Built on open Hermes models
Capable general reasoning
Flexible, open-model foundation
Hosted with apps wired in as tools

Frequently asked questions

Build a custom Hermes agentQdrant integration

Open your Hermes agent in one click

NoClick runs Hermes for you with Qdrant wired in as tools. Connect your account and run.