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Vinkius

FastGPT Connector for AI agents.

12 live capabilities

Manage RAG pipelines and knowledge base datasets from your AI client.

Live agent request FastGPT / Connector

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AI Agent

Why people use FastGPT

Stop Manually Updating FastGPT Knowledge Bases with Data Entry

This Connector changes that by letting your AI agent do the heavy lifting. You can tell your agent to push data, create new datasets, or update records directly. You get a unified workflow where your agent handles the data management while you focus on the actual content.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get a direct line of command to your FastGPT RAG infrastructure from your favorite AI client.

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

One account · 5,900+ Connectors

  1. Real-world use case 01

    Bulk document ingestion

    A knowledge engineer needs to update 50 internal PDFs.

  2. Real-world use case 02

    Retrieval debugging

    A developer wants to see why a RAG response was wrong.

  3. Real-world use case 03

    Application auditing

    An admin needs to audit all active apps.

Complete set · 12capabilities

The complete FastGPT capability set.

These are the exact actions your AI can choose when you ask it to work with FastGPT.

Capability set01 / 03

01—04

4 capabilities in this set.

Part of 12 available through FastGPT.

  1. 01 Capability

    Get dataset detail

    View the configuration and metadata for a specific knowledge base dataset. It helps you see how your data is structured.

  2. 02 Capability

    List apps

    Get a complete list of all AI applications currently hosted on your FastGPT instance. It helps you keep track of your active capabilities.

  3. 03 Capability

    List dataset data

    View all individual data items currently stored within a specific dataset. This lets you see exactly what your agent can access.

  4. 04 Capability

    List datasets

    List all your knowledge base datasets with options to filter by parent ID or keyword. This helps you organize large data inventories.

Capability set02 / 03

05—08

4 capabilities in this set.

Part of 12 available through FastGPT.

  1. 05 Capability

    Push dataset data

    Add new content or update existing records in your knowledge base datasets. This is the primary way to ingest data via your agent.

  2. 06 Capability

    Search dataset data

    Perform semantic searches against your datasets to test RAG relevance and accuracy. Use this to debug your retrieval quality.

  3. 07 Capability

    Update dataset data

    Modify specific records within a dataset to keep your information current. This ensures your agent always has the latest facts.

  4. 08 Capability

    Get app detail

    Pull specific configuration details for a single AI application. Use this to inspect your current app settings.

Capability set03 / 03

09—12

4 capabilities in this set.

Part of 12 available through FastGPT.

  1. 09 Capability

    Chat completions

    Send messages to a FastGPT app while maintaining session context and viewing intermediate steps. This is useful for interacting with your RAG-powered chat apps.

  2. 10 Capability

    Get embeddings

    Generate text embeddings for use in semantic search tasks outside of the FastGPT platform. This helps with custom vector work.

  3. 11 Capability

    Create dataset

    Create a new knowledge base dataset to house your documents or data chunks. This is the first step in building a new RAG pipeline.

  4. 12 Capability

    Delete dataset data

    Remove specific data points from a dataset to keep your knowledge base clean. Use this to prune outdated information.

Set up in minutes

One URL. Then ask FastGPT to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use FastGPT 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_5ych6Vwp9PYj4HCpHT5jojSMb56573gZQlH3hDOl/mcp
  1. Step 01

    Open Connectors

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

  2. Step 02

    Add the URL

    Choose Add custom connector, name it FastGPT, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable FastGPT for the conversation.

Where the request belongs

Work FastGPT can move forward.

Built around the request

This is for the RAG developer who's tired of manual data entry and the knowledge engineer who needs to automate documentation syncing across multiple datasets.

01

Knowledge Engineer

Automates the ingestion of company docs into specific datasets on a weekly basis.

02

RAG Developer

Debugs semantic search results and tweaks chunking strategies using the agent.

03

System Integrator

Builds complex workflows where an agent needs to create or update knowledge bases on the fly.

Build the capability set

Add more capabilities.

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

Browse Connectors
Cognita (RAG Framework) logo
01 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.

View Connector
LlamaIndex (AI Data Framework & RAG) logo
02 6 capabilities

LlamaIndex (AI Data Framework & RAG)

Query and manage RAG pipelines via LlamaIndex. execute natural language searches, audit indexed files, and monitor data pipelines.

View Connector
LlamaCloud (Managed RAG & Parsing) logo
03 6 capabilities

LlamaCloud (Managed RAG & Parsing)

Manage RAG pipelines and document parsing via LlamaCloud. orchestrate LlamaParse jobs and audit data ingestion.

View Connector
Jina AI (Search Foundation & LLM Grounding) logo
04 6 capabilities

Jina AI (Search Foundation & LLM Grounding)

Power your RAG and search via Jina AI. generate embeddings, rerank documents, read URLs, and perform semantic web search.

View Connector
VectorShift (AI Workflow & RAG Automation) logo
05 29 capabilities

VectorShift (AI Workflow & RAG Automation)

Automate AI workflows and RAG via VectorShift. manage pipelines, query knowledge bases, and deploy chatbots directly from any AI agent.

View Connector
Amazon Bedrock KB logo
06 6 capabilities

Amazon Bedrock KB

Connect your AI agent to AWS Bedrock Knowledge Bases. execute semantic searches, managed RAG, and sync vector datasources natively.

View Connector

Bring your own AI

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

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • VS Code
  • Windsurf
  • ZCode
  • Cline
  • Zed
  • Continue
  • Kiro
  • Roo Code
  • Zencoder
  • Goose
  • Void
  • Augment Code
  • Amp
  • Qodo
  • Tabnine
  • Pieces
  • Sourcegraph Cody
  • JetBrains
  • Warp
  • Amazon Q
  • Antigravity
  • BoltAI
  • Raycast
  • Jan
  • LM Studio
  • AnythingLLM
  • Open WebUI
  • Msty
  • Cherry Studio
  • LibreChat
  • TypingMind
  • Chorus
  • 5ire
  • n8n
  • LangChain
  • LlamaIndex
  • CrewAI
  • Vercel AI SDK

Before you connect

Questions about FastGPT.

The practical details behind the request, access and result.

What can I do with the FastGPT MCP?

This Connector lets you manage your FastGPT knowledge base directly through your AI agent. You can create datasets, push new information, and search your data without leaving your chat interface.

Can I use this to update my knowledge base?

Yes, you can use your agent to update existing records or push new content into your datasets to keep your information current.

How does this help with RAG accuracy?

It allows you to run semantic searches to see exactly how your agent retrieves information, making it much easier to debug and optimize your RAG results.

Can I create new datasets through my AI agent?

Absolutely. You can ask your agent to create a new knowledge base dataset for any project, and it will handle the setup for you.

Does this support session tracking?

Yes, when you use the chat capabilities, your agent can maintain session context and show you the intermediate steps the application takes to generate a response.

Can I use this for semantic search?

Yes, you can perform semantic searches against your datasets to test relevance and accuracy for specific queries.

How do I connect this to my FastGPT account?

You just need to provide your FastGPT Base URL and your API key from your app settings to your AI client to get started.

Can I use this with my self-hosted FastGPT instance?

Yes! Simply provide your custom domain in the Base URL field (e.g., https://fastgpt.mycompany.com). The Connector will route all requests to your specific instance.

How do I add new data to an existing dataset?

Use the push_dataset_data capability. You can send a JSON array of objects containing the text content to be indexed. FastGPT will handle the chunking and embedding automatically.

What is the 'goods_sign' used for in Pinduoduo capabilities?

Wait, this is the FastGPT FAQ. For FastGPT, you mostly need Dataset IDs and App IDs. The 'goods_sign' is specific to the Pinduoduo MCP. Always check you are using the correct capabilities for the specific platform.

One connection away

Give your agent a direct line to FastGPT.

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

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