VectorShift (AI Workflow & RAG Automation) Connector for AI agents.

29 live capabilities

Manage RAG workflows and automate AI pipelines from your chat interface.

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Why people use VectorShift (AI Workflow & RAG Automation)

VectorShift for RAG and Knowledge Management

This Connector changes that by letting you manage your entire knowledge layer through your agent. You can create knowledge bases and index new documents with a single command. Instead of manual copy-pasting, your agent uses query_knowledge_base to find the exact info it needs, grounding your answers in real data instantly.

What Vinkius changes

You get a direct command line to your entire VectorShift automation suite.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

Real-world use case 01

Automating a high-volume data extraction

An ops engineer needs to pull data from 500 URLs.
Real-world use case 02

Updating a company wiki for a RAG bot

A product manager wants the chatbot to know about a new refund policy.
Real-world use case 03

Cleaning messy user data before processing

A developer needs to strip PII from logs.

Complete set · 29capabilities

The complete VectorShift (AI Workflow & RAG Automation) capability set.

These are the exact actions your AI can choose when you ask it to work with VectorShift (AI Workflow & RAG Automation).

Capability set01 / 08

01—04

4 capabilities in this set.

Part of 29 available through VectorShift (AI Workflow & RAG Automation).

01 Capability
Delete knowledge base documents
Delete specific files from a knowledge base by their ID. This helps you keep your data clean and relevant.
02 Capability
List knowledge bases
See all your available knowledge bases. Use this to manage your different data silos.
03 Capability
Upload chatbot files
Upload files to a specific chatbot session. This lets you give the bot immediate context for a conversation.
04 Capability
Bulk run pipeline
Run multiple pipeline instances at the same time. This is great for processing large batches of data quickly.

Capability set02 / 08

05—08

4 capabilities in this set.

Part of 29 available through VectorShift (AI Workflow & RAG Automation).

05 Capability
Create chatbot
Set up a new chatbot instance. Use this to quickly spin up a new conversational point of contact.
06 Capability
Create knowledge base
Build a new vector-based knowledge base. This is your first step for grounding your AI in specific data.
07 Capability
Create pipeline
Build a new multi-step AI workflow. Use this to define the logic for your automated processes.
08 Capability
Create transformation
Create a custom Python or JS transformation. This lets you handle complex data logic before it hits your model.

Capability set03 / 08

09—12

4 capabilities in this set.

Part of 29 available through VectorShift (AI Workflow & RAG Automation).

09 Capability
Delete chatbot
Remove a chatbot from your account. Use this to clean up old or unused conversational instances.
10 Capability
Delete knowledge base
Remove an entire knowledge base. Use this when you no longer need a specific data set indexed.
11 Capability
Delete pipeline
Remove a specific pipeline from your list. Use this to keep your workspace organized.
12 Capability
Delete transformation
Remove a custom transformation. Use this to clear out old logic or scripts.

Capability set04 / 08

13—16

4 capabilities in this set.

Part of 29 available through VectorShift (AI Workflow & RAG Automation).

13 Capability
Get chatbot
Fetch the details of a specific chatbot. Use this to check the status or configuration of an existing bot.
14 Capability
Get knowledge base
Fetch details for a specific knowledge base. This helps you verify the status of your indexed data.
15 Capability
Get pipeline
Fetch the details of a specific pipeline. Use this to check the configuration of a workflow you're building.
16 Capability
Get transformation
Fetch the details of a specific transformation. Use this to review the logic of your custom scripts.

Capability set05 / 08

17—20

4 capabilities in this set.

Part of 29 available through VectorShift (AI Workflow & RAG Automation).

17 Capability
Index knowledge base
Add files or URLs to your knowledge base. This is how you feed your RAG system new information.
18 Capability
List chatbots
See a list of all your chatbots. Use this to get an overview of your active conversational agents.
19 Capability
List knowledge base documents
Find all the documents currently in a knowledge base. This helps you audit what data your AI can see.
20 Capability
List pipelines
See a list of all your pipelines. Use this to keep track of your active AI workflows.

Capability set06 / 08

21—23

3 capabilities in this set.

Part of 29 available through VectorShift (AI Workflow & RAG Automation).

21 Capability
List transformations
See a list of all your custom transformations. Use this to manage your collection of data logic scripts.
22 Capability
Pause pipeline
Pause a pipeline that's currently running. Use this to stop execution without deleting the progress.
23 Capability
Query knowledge base
Perform a semantic search on a knowledge base. This is how you get grounded answers from your data.

Capability set07 / 08

24—26

3 capabilities in this set.

Part of 29 available through VectorShift (AI Workflow & RAG Automation).

24 Capability
Resume pipeline
Resume a pipeline that was paused. Use this to pick up where the workflow left off.
25 Capability
Run chatbot
Send a message to a chatbot and get a response. Use this to test your bot's behavior in real-time.
26 Capability
Run pipeline
Execute a pipeline with specific inputs. This starts the actual automation process for your data.

Capability set08 / 08

27—29

3 capabilities in this set.

Part of 29 available through VectorShift (AI Workflow & RAG Automation).

27 Capability
Run transformation
Execute a custom transformation with your inputs. Use this to run specific data logic on demand.
28 Capability
Terminate chatbot
End an active chatbot session. Use this to clear out a specific conversation or session.
29 Capability
Terminate pipeline
Stop a pipeline that's currently running. Use this to kill a process that isn't behaving correctly.

Set up in minutes

One URL. Then ask VectorShift (AI Workflow & RAG Automation) to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use VectorShift (AI Workflow & RAG Automation) from the conversation.

Choose your client

Live preview

Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP

https://edge.vinkius.com/vk_preview_EmQ0ykbVFnJJJOx8Wrsr9PBOJ4yiohOhm84Pa96G/mcp

Step 01

Open Connectors

In Claude Web or Claude Desktop, open Settings and choose Connectors.
Step 02

Add the URL

Choose Add custom connector, name it VectorShift (AI Workflow & RAG Automation), and paste the URL above.
Step 03

Turn it on in chat

Select +, open Connectors, and enable VectorShift (AI Workflow & RAG Automation) for the conversation.

ChatGPT · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP

https://edge.vinkius.com/vk_preview_EmQ0ykbVFnJJJOx8Wrsr9PBOJ4yiohOhm84Pa96G/mcp

Step 01

Open MCP settings

On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
Step 02

Add the URL

Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the VectorShift (AI Workflow & RAG Automation) URL.
Step 03

Save and start

Save the connection and enable VectorShift (AI Workflow & RAG Automation) in your conversation. Desktop may ask you to restart once.

Cursor · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "vectorshift-ai-workflow-rag-automation": {
      "url": "https://edge.vinkius.com/vk_preview_EmQ0ykbVFnJJJOx8Wrsr9PBOJ4yiohOhm84Pa96G/mcp"
    }
  }
}

Step 01

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Step 02

Add the server config

Paste the JSON configuration above into the mcp.json file that opens
Step 03

Save the file

Cursor will automatically detect the new Connector
Step 04

Start using VectorShift (AI Workflow & RAG Automation)

Open Agent mode in chat and ask: "Using VectorShift (AI Workflow & RAG Automation), help me...". 29 tools available

VS Code Copilot · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "vectorshift-ai-workflow-rag-automation": {
      "url": "https://edge.vinkius.com/vk_preview_EmQ0ykbVFnJJJOx8Wrsr9PBOJ4yiohOhm84Pa96G/mcp"
    }
  }
}

Step 01

Create MCP config

Create a .vscode/mcp.json file in your project root
Step 02

Add the server config

Paste the JSON configuration above
Step 03

Enable Agent mode

Open GitHub Copilot Chat and switch to Agent mode using the dropdown
Step 04

Start using VectorShift (AI Workflow & RAG Automation)

Ask Copilot: "Using VectorShift (AI Workflow & RAG Automation), help me...". 29 tools available

Windsurf · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "vectorshift-ai-workflow-rag-automation": {
      "url": "https://edge.vinkius.com/vk_preview_EmQ0ykbVFnJJJOx8Wrsr9PBOJ4yiohOhm84Pa96G/mcp"
    }
  }
}

Step 01

Open MCP Settings

Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Step 02

Add the server

Paste the JSON configuration above into mcp_config.json
Step 03

Save and reload

Windsurf will detect the new server automatically
Step 04

Start using VectorShift (AI Workflow & RAG Automation)

Open Cascade and ask: "Using VectorShift (AI Workflow & RAG Automation), help me...". 29 tools available

Cline · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "vectorshift-ai-workflow-rag-automation": {
      "url": "https://edge.vinkius.com/vk_preview_EmQ0ykbVFnJJJOx8Wrsr9PBOJ4yiohOhm84Pa96G/mcp"
    }
  }
}

Step 01

Open Cline MCP Settings

Click the Connectors icon in the Cline sidebar panel
Step 02

Add remote server

Click "Add Connector" and paste the configuration above
Step 03

Enable the server

Toggle the server switch to ON
Step 04

Start using VectorShift (AI Workflow & RAG Automation)

Ask Cline: "Using VectorShift (AI Workflow & RAG Automation), help me...". 29 tools available

Claude Code · Terminal command

Official guide ↗

Advanced setup

claude mcp add vectorshift-ai-workflow-rag-automation --transport http "https://edge.vinkius.com/vk_preview_EmQ0ykbVFnJJJOx8Wrsr9PBOJ4yiohOhm84Pa96G/mcp"

Step 01

Install Claude Code

Run npm install -g @anthropic-ai/claude-code if not already installed
Step 02

Add the Connector

Run the command above in your terminal
Step 03

Verify the connection

Run claude mcp to list connected servers, or type /mcp inside a session
Step 04

Start using VectorShift (AI Workflow & RAG Automation)

Ask Claude: "Using VectorShift (AI Workflow & RAG Automation), show me...". 29 tools are ready

Where the request belongs

Work VectorShift can move forward.

Built around the request

This is for the AI engineer who is tired of manual data indexing and the ops person who needs to trigger complex workflows without a UI.

01

AI Engineer

Testing RAG pipelines and indexing new datasets while staying inside the code editor.

02

Ops Manager

Triggering bulk data extractions and monitoring pipeline health from a simple chat.

03

Product Manager

Querying internal documentation to get quick answers on product specs.

Build the capability set

Each Connector adds new actions and data without changing how you work.

Browse Connectors

01 6 capabilities

R2R

Equip your AI with direct access to your R2R engine. execute vector searches, run precise RAG queries, and manage your documents.

02 7 capabilities

Cognita (RAG Framework)

Manage modular RAG via Cognita. list collections, ingest data sources, and perform AI-driven Q&A directly from any AI agent.

03 12 capabilities

FlowiseAI

Build LLM orchestration flows visually with a drag-and-drop interface for creating AI chatbots, agents, and RAG pipelines.

04 7 capabilities

Haystack (deepset Cloud)

Build and manage AI-powered search and RAG pipelines via deepset Cloud. search documents, run pipelines, and manage workspaces.

05 12 capabilities

FastGPT

Manage FastGPT Knowledge Bases. automate dataset creation, document ingestion, and RAG search directly from any AI agent.

06 10 capabilities

Cody AI

Enable your AI agent to manage knowledge-base bots, import documents, and query trained AI assistants via the Cody AI API.

Bring your own AI

Change the model, client or framework. Keep VectorShift connected.

Before you connect

Questions about VectorShift.

The practical details behind the request, access and result.

Can I use VectorShift MCP to manage my RAG pipelines?

Yes. This Connector gives your AI agent the ability to create, run, and monitor RAG pipelines directly. You can manage the entire lifecycle of your data workflows without leaving your chat interface.

How does the VectorShift MCP handle my company's private data?

It connects to your existing VectorShift account. You can use it to index your private files and URLs into knowledge bases, which your agent then queries to provide grounded, accurate responses.

Can I run custom code with the VectorShift MCP?

Yes, you can. The Connector includes capabilities to create and execute custom Python and JavaScript transformations, allowing your agent to perform complex data processing as part of an automated workflow.

Is the VectorShift MCP good for bulk processing?

It is designed for that. You can use the bulk_run_pipeline capability to execute multiple instances of a pipeline in parallel, making it ideal for high-volume data tasks.

Can I pause a running workflow using VectorShift MCP?

Yes, you can. If a pipeline hits a point where you need to intervene, you can use the pause_pipeline capability to stop it and resume_pipeline once you're ready to continue.

Does the VectorShift MCP support multiple knowledge bases?

Yes, you can create and manage multiple knowledge bases. This allows you to separate different types of data, like HR docs, product specs, and customer support logs, into distinct silos.

How do I search for specific information within my VectorShift knowledge base?

Use the query_knowledge_base capability with your Knowledge Base ID and the search query. The agent will perform a semantic search and return the most relevant data chunks.

Can I trigger a specific AI workflow with custom parameters?

Yes! Use the run_pipeline capability. Provide the Pipeline ID and a JSON object mapping your input names to their respective values to start the execution.

Is it possible to add new documents to a knowledge base through the agent?

Absolutely. Use the index_knowledge_base capability to add data (such as URLs or file content) to an existing knowledge base for real-time RAG updates.

One connection away

Give your agent a direct line to VectorShift.

Connect VectorShift once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available