> ## Documentation Index
> Fetch the complete documentation index at: https://www.edenai.co/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# open-connector

> Use open-connector with Eden AI to expose 500+ AI models through a self-hosted gateway with SDK, CLI, MCP and HTTP access.

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<TechArticleSchema title={"open-connector"} description={"Use open-connector with Eden AI to expose 500+ AI models through a self-hosted gateway with SDK, CLI, MCP and HTTP access."} path="v3/integrations/open-connector" articleSection="AI Gateway" about={"LLM Gateway Integration"} proficiencyLevel="Intermediate" keywords={["Eden AI", "AI API", "open-connector", "LLM Gateway", "MCP"]} datePublished="2026-07-27T00:00:00Z" dateModified="2026-07-27T00:00:00Z" />

Use open-connector with Eden AI to expose 500+ AI models through a self-hosted gateway with SDK, CLI, MCP and HTTP access.

## Overview

[open-connector](https://github.com/oomol-lab/open-connector) is an open-source gateway connecting 1000+ SaaS providers to AI agents via SDK, CLI, MCP and HTTP. Eden AI ships as a **built-in connector**, so any agent wired through open-connector reaches models from OpenAI, Anthropic, Google, Mistral and more behind one key, with EU-based, GDPR-aligned inference and per-request cost visibility.

## Installation

open-connector is a self-hosted gateway, distributed as a Docker image:

<CodeGroup>
  ```bash Docker theme={null}
  docker compose up
  ```
</CodeGroup>

This pulls `ghcr.io/oomol-lab/open-connector:latest` and serves the console and API at `http://localhost:3000`.

## Quick Start

Store your Eden AI key as a connection credential, then call the `edenai` service:

<CodeGroup>
  ```bash Add credential theme={null}
  curl -s -X PUT http://localhost:3000/api/connections/edenai \
    -H 'content-type: application/json' \
    -d '{"authType":"api_key","values":{"apiKey":"your_api_key_here"}}'
  ```

  ```bash Call Eden AI theme={null}
  curl -s -X POST http://localhost:3000/v1/actions/edenai.create_chat_completion \
    -H 'content-type: application/json' \
    -d '{
      "input": {
        "model": "openai/gpt-5.5",
        "messages": [{"role": "user", "content": "Hello! How are you?"}]
      }
    }'
  ```
</CodeGroup>

The base URL (`https://api.edenai.run/v3`) is built into the connector — no extra configuration needed. The response includes the standard OpenAI-compatible fields plus a top-level `cost` field with the Eden AI billed cost.

## Available Models

The `edenai` service exposes `edenai.list_models` and `edenai.create_chat_completion`. Use the `provider/model` format for any Eden AI model:

**OpenAI**

* `openai/gpt-5.5`
* `openai/gpt-5-mini`

**Anthropic**

* `anthropic/claude-sonnet-5`
* `anthropic/claude-haiku-4-5`

**Google**

* `google/gemini-2.5-pro`
* `google/gemini-3.5-flash`

**Mistral**

* `mistral/mistral-large-2512`
* `mistral/mistral-small-2603`

## Credentials

Unlike most integrations, open-connector stores the Eden AI key as a **connection credential** through its API rather than an environment variable:

<CodeGroup>
  ```bash Update credential theme={null}
  curl -s -X PUT http://localhost:3000/api/connections/edenai \
    -H 'content-type: application/json' \
    -d '{"authType":"api_key","values":{"apiKey":"your_api_key_here"}}'
  ```
</CodeGroup>

## Next Steps

* [Lynkr](/docs/v3/integrations/lynkr) - Another self-hosted LLM gateway
* [Bifrost](/docs/v3/integrations/bifrost) - Custom-provider LLM gateway
* [Chat Completions](/docs/v3/llms/chat-completions) - Core LLM endpoint