Writer (AI Enterprise LLM) Connector for AI agents.

24 live capabilities

Connect your agent to enterprise models and Knowledge Graphs for RAG.

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Why people use Writer (AI Enterprise LLM)

Writer for Enterprise RAG and Knowledge Graphs

This Connector changes that by letting your agent interact with Knowledge Graphs. You can structure your data, connect related points, and query your internal docs for precise answers. You get a reliable source of truth that actually knows your business.

What Vinkius changes

You get a bridge between your internal data and enterprise-grade AI models.

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

One account · 6,100+ Connectors

Real-world use case 01

RAG for internal HR policies

An HR manager asks the agent about a specific policy.
Real-world use case 02

Automated content production

A content lead wants to generate 50 product descriptions.
Real-world use case 03

Web-enhanced market research

A researcher needs the latest news on a topic.

Complete set · 24capabilities

The complete Writer (AI Enterprise LLM) capability set.

These are the exact actions your AI can choose when you ask it to work with Writer (AI Enterprise LLM).

Capability set01 / 06

01—04

4 capabilities in this set.

Part of 24 available through Writer (AI Enterprise LLM).

01 Capability
Download file
Get the binary content of a specific file. Use this when you need to pull raw data.
02 Capability
Analyze vision
Use a prompt to analyze images or documents. This lets your agent see and describe visual data.
03 Capability
Ask question
Query one or more Knowledge Graphs for an answer. This is the primary way to perform RAG.
04 Capability
Chat completion
Generate a chat response using Writer's enterprise models. This is perfect for building conversational interfaces.

Capability set02 / 06

05—08

4 capabilities in this set.

Part of 24 available through Writer (AI Enterprise LLM).

05 Capability
Generate application content async
Start a long-running no-code application job. This returns a job ID for you to check later.
06 Capability
Generate application content
Run a no-code application job synchronously. Use this for quick results from your pre-built apps.
07 Capability
Get application job
Check the status and results of a specific application job. This is how you track async tasks.
08 Capability
Get application
See the configuration and inputs for a specific application. Use this to understand how an app is set up.

Capability set03 / 06

09—12

4 capabilities in this set.

Part of 24 available through Writer (AI Enterprise LLM).

09 Capability
Get file
Get the metadata for a specific file. This is useful for organizing your document library.
10 Capability
List application jobs
See a list of all jobs for a specific application. Use this to monitor high-volume task runs.
11 Capability
List applications
See all your deployed no-code agents or applications. This helps you keep track of your automated workflows.
12 Capability
List files
Get a paginated list of all your uploaded files. Use this to audit your current storage.

Capability set04 / 06

13—16

4 capabilities in this set.

Part of 24 available through Writer (AI Enterprise LLM).

13 Capability
List graphs
See all the Knowledge Graphs you've created. This helps you manage your RAG data sources.
14 Capability
List models
See which Writer models are currently available. This ensures you are using the latest enterprise tech.
15 Capability
Remove file from graph
Take a specific file out of a Knowledge Graph. Use this to update your RAG context without deleting the file.
16 Capability
Retry application job
Run a failed application job again. This helps you recover from temporary errors in your workflows.

Capability set05 / 06

17—20

4 capabilities in this set.

Part of 24 available through Writer (AI Enterprise LLM).

17 Capability
Text completion
Generate a text completion for a single prompt. Use this for straightforward, one-off text generation.
18 Capability
Translate text
Translate text between different supported languages. This is great for global content teams.
19 Capability
Upload file
Upload a file to use for Knowledge Graphs or vision tasks. This is the first step in building your RAG context.
20 Capability
Web search
Search the internet for a specific query. Use this to give your agent access to real-time information.

Capability set06 / 06

21—24

4 capabilities in this set.

Part of 24 available through Writer (AI Enterprise LLM).

21 Capability
Create graph
Build a new Knowledge Graph from scratch. Use this to organize your data for RAG.
22 Capability
Delete file
Permanently remove a file from your storage. This helps keep your graph context clean.
23 Capability
Parse pdf
Convert a PDF into text or markdown format. This is a legacy capability for extracting content from documents.
24 Capability
Add file to graph
Attach an uploaded file to a specific Knowledge Graph. This connects your documents to your RAG system.

Where the request belongs

Work Writer can move forward.

Built around the request

This is for the enterprise developer who needs to build RAG apps without the headache of manual data plumbing, or the content lead who needs to maintain brand consistency across huge volumes of text.

01

Enterprise Developer

Builds RAG-powered apps using Knowledge Graphs and secure models on a Tuesday afternoon.

02

Content Strategist

Automates high-quality content generation across multiple channels to stay ahead of deadlines.

03

Data Engineer

Manages document pipelines and connects files to Knowledge Graphs to keep data flowing.

Build the capability set

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

Browse Connectors

01 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.

02 5 capabilities

Tome (AI Storytelling)

Generate and manage AI-powered presentations via Tome. list workspaces, manage tomes, and add pages 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 6 capabilities

Dify

Manage agentic workflows via Dify. send chat messages, track conversations, audit app parameters, and handle file uploads directly from any AI agent.

05 12 capabilities

FastGPT

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

06 5 capabilities

Cohere (AI Platform)

Power enterprise AI via Cohere. generate text, perform chat completions, reorder documents, and manage embeddings directly from any AI agent.

Bring your own AI

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

Before you connect

Questions about Writer.

The practical details behind the request, access and result.

How does the Writer MCP help with RAG?

It provides capabilities to create Knowledge Graphs and ask questions against them, making it easy to build Retrieval-Augmented Generation systems.

Can I use this Connector to manage my company's documents?

Yes, you can upload, list, and delete files to keep your model context and Knowledge Graphs organized.

Does the Writer MCP support web searching?

Yes, it includes a web_search capability so your agent can pull in real-time information from the internet.

Can I run long-running tasks with the Writer MCP?

You can use the async application capabilities to start a job, get a job ID, and check the status later.

Is this Connector good for multi-language content?

Yes, it includes a translation capability that lets your agent convert text between supported languages quickly.

How do I use the Writer MCP for image analysis?

You can use the vision capability to ask your agent questions about images or documents you've uploaded.

How do I see which Palmyra models are available in my account?

Use the list_models capability. It will return a list of all active models in your Writer account, such as palmyra-x5 or palmyra-med.

Can I use my own documents for AI responses?

Yes. First, use upload_file to add your documents, then create_graph and add_file_to_graph to build a Knowledge Graph for RAG-based querying.

Does this support conversational history?

Yes, the chat_completion capability accepts a messages array, allowing you to maintain full context for multi-turn dialogues with the model.

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