Do I need to write any code to use this MCP?

No. You connect your Anthropic account, and your AI client handles the API calls. You interact with the capabilities—like sending messages or counting tokens—using natural conversation, not code.

What is the difference between send_message and create_batch_message?

Send_message is for single, immediate conversations. Create_batch_message is for running many independent prompts at once. Batching is much more cost-effective when you have a large volume of data.

Can I check if a batch job finished?

Yes. After creating a batch, you use get_batch_message with the returned batch ID. This tells you the status, including total successes and errors.

Is this just a simple API key connector?

It's more than that. It acts as an LLM orchestration layer. It lets your AI client manage the entire workflow, from model discovery to running complex, multi-step jobs.

What happens if I submit a batch job by mistake?

You can use cancel_batch_message. Just provide the batch ID, and the MCP will request that the processing stops, helping you save 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.

An astronaut overseeing a futuristic data hub

Download PDF Markdown Version

Connect Anthropic (Alternative) to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Use Claude's power directly from your AI client.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 6 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through Anthropic.

01
Create batch message
Create a batch of message requests to Claude. This is the most cost-effective way to process many independent prompts at once. It returns a batch ID that you use to track progress.
02
Get batch message
Check the status of a batch message request using the batch ID. This tells you if the job succeeded, failed, or is still in progress.
03
List models
Use this capability to list all available Anthropic Claude models. It returns the model ID, display name, and capabilities, letting you know exactly which models you can use with the send_message capability.

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through Anthropic.

04
Send message
Send a message to Claude using a specified model ID. You can configure the system prompt, set a maximum token count, and adjust the temperature. This returns the assistant's response text directly.
05
Cancel batch message
Stop a batch message request that is still running. Provide the batch ID if you need to cancel processing to save costs.
06
Count tokens
Count tokens in a message before sending it to Claude. This is useful for estimating API costs and making sure your input fits within the context window.

Real work

What teams actually run

Content Moderation Pipeline

Send thousands of user-submitted texts to Claude via batch processing to check for policy violations, saving time and API credits.

Data Extraction Testing

Use the send_message capability to test how different Claude models extract specific data points from varied document types.

API Cost Auditing

Before running a large prompt, use count_tokens to predict the exact token usage and associated cost.

Automated Reporting

Run a batch of prompts to summarize weekly reports from different departments, then check the status with get_batch_message.

Automate a task

Put Anthropic to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Anthropic works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put Anthropic to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

895ms average. Fast in production.

Anthropic is checked daily against the live service.

Daily averagePeak 1087ms

Oct 3Today

Fastest day: 651ms
Slowest day: 1087ms
14-day trend: Improving-17%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Anthropic, so you can see the experience inside your AI.

It does not authenticate your account with Anthropic. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Anthropic Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_olS3uDDLdOw9uiZoTqVqVIoK0UcivzobkVz8mrNA/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — Anthropic capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "anthropic-alternative-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_olS3uDDLdOw9uiZoTqVqVIoK0UcivzobkVz8mrNA/mcp"
    }
  }
}

Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Anthropic in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Anthropic owners hand off.

This MCP is built for technical roles that handle large volumes of text data or require model flexibility. If your job involves testing multiple LLM capabilities or running scheduled, high-throughput tasks, this connector handles the complexity so you don't have to write the underlying API calls.

01
Developers
You can quickly send messages, count tokens, and manage batch requests without writing any HTTP code.
02
ML Engineers
You can discover available models, compare capabilities, and batch-process many prompts efficiently for testing.
03
Product Teams
You can review model outputs, track token usage, and manage batch processing jobs directly through conversation.

FAQ

Questions Anthropic owners ask.

01
Do I need to write any code to use this MCP?
No. You connect your Anthropic account, and your AI client handles the API calls. You interact with the capabilities—like sending messages or counting tokens—using natural conversation, not code.
02
What is the difference between send_message and create_batch_message?
Send_message is for single, immediate conversations. Create_batch_message is for running many independent prompts at once. Batching is much more cost-effective when you have a large volume of data.
03
Can I check if a batch job finished?
Yes. After creating a batch, you use get_batch_message with the returned batch ID. This tells you the status, including total successes and errors.
04
Is this just a simple API key connector?
It's more than that. It acts as an LLM orchestration layer. It lets your AI client manage the entire workflow, from model discovery to running complex, multi-step jobs.
05
What happens if I submit a batch job by mistake?
You can use cancel_batch_message. Just provide the batch ID, and the MCP will request that the processing stops, helping you save costs.
06
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.
07
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.
08
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?"}].
09
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.

Explore

More in AI Frontier

Connect Anthropic to Claude, Cursor, ChatGPT & more

Your AI does the work. We keep it safe and sound.

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-03

Create batch message

Get batch message

List models

04-06

Send message

Cancel batch message

Count tokens

What teams actually run

Content Moderation Pipeline

Data Extraction Testing

API Cost Auditing

Automated Reporting

Building your own app? The connector is yours to use.

Anthropic Connector

Claude Desktop

Developers

ML Engineers

Product Teams

Do I need to write any code to use this MCP?

What is the difference between send_message and create_batch_message?

Can I check if a batch job finished?

Is this just a simple API key connector?

What happens if I submit a batch job by mistake?

How do I get an Anthropic API Key?

What models are available?

Can I send multi-turn conversations?

How does batch processing work?

Humanloop (LLM Prompt Management API) AI Connector

Anthropic AI Connector

Prompt Template Reuse Analyzer AI Connector

Langfuse (LLM Tracing & Evals) AI Connector

Suggestions

Datadog AI (LLM Observability) AI Connector

Prompt Token Analyzer AI Connector

LangSmith (LLM Observability & Hub) AI Connector

Portkey AI Connector