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Vinkius

Anthropic Connector for AI agents.

6 live capabilities

Manage Claude models and batch prompts directly from your favorite agent.

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AI Agent

Why people use Anthropic

Anthropic for Claude Model Orchestration

This Connector puts everything into your agent's workspace. You can list models, count tokens, and manage batches with simple commands. It turns your agent into a full orchestration layer for your LLM needs.

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

What Vinkius changes

You get a direct line to Claude's models without the overhead of manual request management.

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

One account · 5,900+ Connectors

  1. Real-world use case 01

    Batching Prompt Evaluations

    An ML engineer uses `create_batch_message` to run 500 different prompts across multiple models to compare accuracy scores for a new release.

  2. Real-world use case 02

    Cost-Conscious App Development

    A developer uses `count_tokens` to ensure a user's long document fits within the Claude context window before attempting to summarize it for a customer.

  3. Real-world use case 03

    Model Exploration

    A product team uses `list_models` to find the right balance between speed and reasoning for a new customer service bot they are building.

Complete set · 6capabilities

The complete Anthropic capability set.

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

Capability set01 / 02

01—03

3 capabilities in this set.

Part of 6 available through Anthropic.

  1. 01 Capability

    Get batch message

    Check the progress and results of a submitted batch to see what succeeded or failed. Use this to track your long-running jobs.

  2. 02 Capability

    List models

    See all available Claude models, their IDs, and their specific capabilities in one list. This helps you find the right model for your specific task.

  3. 03 Capability

    Send message

    Send a direct message to a Claude model with custom system prompts, temperature, and max tokens. This is the primary way to get a response from Claude.

Capability set02 / 02

04—06

3 capabilities in this set.

Part of 6 available through Anthropic.

  1. 04 Capability

    Cancel batch message

    Stop an active batch of requests to save on costs if you realize a mistake was made. This is useful for halting large jobs immediately.

  2. 05 Capability

    Count tokens

    Get the exact input token count for a message to stay within context limits and manage your budget. It helps you estimate costs before you hit send.

  3. 06 Capability

    Create batch message

    Queue up multiple independent prompts for cost-effective, asynchronous processing by Claude. This is the best way to handle many requests at once.

Set up in minutes

One URL. Then ask Anthropic to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Anthropic 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_olS3uDDLdOw9uiZoTqVqVIoK0UcivzobkVz8mrNA/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 Anthropic, and paste the URL above.

  3. Step 03

    Turn it on in chat

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

Where the request belongs

Work Anthropic can move forward.

Built around the request

The developer tired of writing boilerplate request code for every LLM interaction, the ML engineer managing hundreds of prompts for evaluation, and the product manager who needs to track token costs without a spreadsheet.

01

ML Engineer

Managing large-scale prompt evaluations and batching requests for model testing on a Tuesday afternoon.

02

Backend Developer

Integrating Claude into a production app without building a custom request wrapper from scratch.

03

Data Scientist

Estimating context window limits and costs before running large data processing jobs on Claude.

Build the capability set

Add more capabilities.

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

Browse Connectors
Anthropic logo
01 8 capabilities

Anthropic

Interact with Claude models via the Anthropic Messages API. send prompts, manage batches, and monitor rate limits directly.

View Connector
OpenAI logo
02 13 capabilities

OpenAI

Manage OpenAI resources via API. list models, monitor fine-tunes, manage batches and inspect Assistants from any AI agent.

View Connector
Keywords AI logo
03 11 capabilities

Keywords AI

Monitor and optimize your LLM API usage with a unified gateway that tracks costs, latency, and model performance across providers.

View Connector
Poe logo
04 10 capabilities

Poe

Manage AI chatbots on Poe. create bots, query other AI models, monitor messages, and track usage stats.

View Connector
Hugging Face LLM logo
05 8 capabilities

Hugging Face LLM

Connect Hugging Face LLM to any AI agent via MCP.

View Connector
Forefront logo
06 10 capabilities

Forefront

Access Forefront AI models directly from your agent. generate chat completions, manage fine-tuning jobs, and collect LLM outputs with pipelines.

View Connector

Bring your own AI

Change the model, client or framework. Keep Anthropic 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 Anthropic.

The practical details behind the request, access and result.

What is the Anthropic MCP?

It's a way to connect Claude models directly to your AI agent. It lets you send messages, count tokens, and manage batches without having to write your own API code.

Can I use the Anthropic MCP in Cursor?

Yes, you can connect it to Cursor or any other MCP-compatible client. This lets you use Claude's capabilities directly within your coding environment.

How do I manage costs with the Anthropic MCP?

You can use the token counting feature to see exactly how much a prompt will cost before you send it. You can also use the batch capabilities to run many prompts more efficiently.

Can I run many prompts at once with this?

Yes, that's one of its main features. You can create batches of independent prompts and have your agent process them asynchronously for you.

How do I see which Claude models are available?

You can just ask your agent to list the models. It will show you all the available IDs and what each model is capable of doing.

Can I stop a batch if I make a mistake?

Yes, you can use the batch cancellation capability to stop an active job immediately. This is helpful if you notice an error in a large batch and want to save on costs.

How do I get an Anthropic API Key?

Log in to the Anthropic Console, go to Account Settings > API Keys and click Create Key. Copy the key immediately. it starts with sk-ant- and won't be shown again. You can also create workspace-scoped keys to control spending by use case.

What models are available?

Use the list_models capability to see all available Claude models. Current models include Claude Sonnet 4, Claude Opus 4 and Claude Haiku variants, each with different capabilities, context windows and pricing. The model ID format is like claude-sonnet-4-20250514.

Can I send multi-turn conversations?

Yes! Pass a messages array with alternating 'user' and 'assistant' roles. Each message has a 'role' and 'content' field. Claude will continue the conversation based on the full message history. Example: [{"role":"user","content":"Hello"},{"role":"assistant","content":"Hi!"},{"role":"user","content":"What's 2+2?"}].

How does batch processing work?

Use create_batch_message with an array of independent message requests. Each request is processed asynchronously and costs 50% less than individual requests. Use get_batch_message to check progress and results. Batches are ideal when you have many unrelated prompts to process.

One connection away

Give your agent a direct line to Anthropic.

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

Explore every Connector No credit card required · Free tier available