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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Ollama with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Run LLM models via Ollama cloud API. generate completions, chat with multimodal models, create embeddings, and inspect model details from any AI agent.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 12 capabilities

The complete Ollama capability set.

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

Capability set01 / 03

01-04

4 capabilities in this set.

Part of 12 available through Ollama.

  1. 01

    Openai embeddings

    Compatible with the OpenAI embeddings API. Supports input as string or array of strings, optional encoding_format and dimensions. Generate embeddings via the OpenAI-compatible endpoint

  2. 02

    Openai list models

    Returns model IDs, creation timestamps, and ownership info. Useful when using OpenAI SDKs that require this endpoint. List models via the OpenAI-compatible endpoint

  3. 03

    Openai responses

    Compatible with the OpenAI Responses API. Uses stream=false for a single complete response. Generate responses via the OpenAI Responses API endpoint

  4. 04

    Chat

    Supports multimodal inputs (images as base64), capability calling, structured outputs (JSON schema), thinking mode, and model options. Pass the full messages array as JSON. Uses stream=false for a single complete response. Generate a chat message in a conversation

Capability set02 / 03

05-08

4 capabilities in this set.

Part of 12 available through Ollama.

  1. 05

    Generate

    Supports images (base64), structured outputs (JSON schema), system prompts, thinking mode, and model options (temperature, top_p, seed, etc.). Uses stream=false for a single complete response. Generate a text completion from a model

  2. 06

    Openai chat completions

    Supports messages, capabilities, temperature, max_tokens, seed, response_format, vision (image_url), and reasoning_effort. Uses stream=false for a single complete response. Generate chat completions via the OpenAI-compatible endpoint

  3. 07

    Openai completions

    Supports prompt, temperature, max_tokens, seed, stop sequences, and suffix (for fill-in-the-middle). Uses stream=false for a single complete response. Generate text completions via the OpenAI-compatible endpoint

  4. 08

    Show model details

    Get detailed information about a specific model

Capability set03 / 03

09-12

4 capabilities in this set.

Part of 12 available through Ollama.

  1. 09

    List running models

    Includes model name, size, VRAM usage, digest, context length, and expiry time (when the model will be unloaded). List models currently loaded in memory

  2. 10

    List models

    List all available models

  3. 11

    Get version

    Useful for diagnostics and compatibility checks. Get the Ollama server version

  4. 12

    Generate embeddings

    Supports single text or array of texts, optional truncation for long inputs, and configurable output dimensions. Use for semantic search, retrieval, and RAG applications. Generate vector embeddings from text using a model

Observed, not estimated

907ms average. Fast in production.

Ollama is checked daily against the live service.

Daily averagePeak 1078ms
Aug 20Today
Fastest day
746ms
Slowest day
1078ms
14-day trend
Slowing+22%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 12 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 Ollama, so you can see the experience inside your AI.

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

Ollama Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_hYpu67YLXAzJ2w17TRhdjXKZcyynLB0AY9L4fYBJ/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Ollama capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ollama-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_hYpu67YLXAzJ2w17TRhdjXKZcyynLB0AY9L4fYBJ/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

FAQ

Questions Ollama owners ask.

  • 01

    How do I get my Ollama API key?

    Visit the Ollama API keys page to create or manage your API key. Once created, copy it and paste it into the API key field in the setup wizard. The key is used as a Bearer token in the Authorization header for all requests to https://ollama.com/api. API keys don't currently expire, but you can revoke them at any time.

  • 02

    Which models are available through this MCP?

    All models available on ollama.com are accessible, including Gemma, GPT-OSS, Qwen, Llama, and many others. Use list_models to see all available models, and show_model_details to inspect a model's capabilities (completion, vision, capabilities), parameter size, quantization level, and architecture details.

  • 03

    Can my AI use vision models to analyze images?

    Yes! The generate and chat capabilities support image inputs as base64-encoded strings. Use a vision-capable model (check with show_model_details. look for 'vision' in capabilities) and pass images in the request. The OpenAI-compatible openai_chat_completions capability also supports image_url content parts for vision models.

  • 04

    What is the difference between native and OpenAI-compatible endpoints?

    The native Ollama endpoints (generate, chat, embed) offer the full feature set including thinking mode, keep_alive control, and detailed response metadata (token counts, durations). The OpenAI-compatible endpoints (/v1/chat/completions, /v1/completions, /v1/embeddings, /v1/responses) provide drop-in compatibility for existing applications built with the OpenAI SDK. they use the same request/response format as OpenAI's API.

  • 05

    Does this MCP support capability calling (function calling)?

    Yes. The chat capability supports capability calling. pass a JSON array of capability definitions in the tools_json parameter. The model will return capability calls in the response when it determines a function should be invoked. The OpenAI-compatible openai_chat_completions capability also supports capabilities via the tools_json parameter.

  • 06

    Can I generate structured JSON output?

    Yes. Both generate and chat capabilities support structured outputs via the format_json parameter. You can pass the string 'json' for basic JSON mode, or a full JSON schema object to enforce a specific output structure. The OpenAI-compatible endpoints also support response_format for structured output.

  • 07

    What is the base URL for API calls?

    All API calls are sent to https://ollama.com/api with the Authorization: Bearer YOUR_API_KEY header. The engine automatically appends the correct path for each endpoint (e.g. /generate, /chat, /v1/chat/completions). This MCP targets the Ollama cloud API. for local Ollama instances, the base URL would be http://localhost:11434/api (no API key required).

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