Continue.dev con Claude, GPT y Gemini

Añade una entrada de models al config.yaml de Continue con provider openai y la base URL de avots, y el asistente de VS Code o JetBrains se ejecuta sobre avots.

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Connect in three fields

Continue lee los modelos desde config.yaml. Añade un proveedor openai que apunte a avots.

FieldValue
Base URLhttps://api.avots.ai/openai/v1
API keyav_mcp_… · get your key
Modelanthropic/claude-sonnet-4.6 or any id from the table below

Setup

1. Abre config.yaml

Abre ~/.continue/config.yaml, el formato actual de configuración de Continue. En Windows es la carpeta .continue en tu perfil de usuario.

2. Añade un modelo openai

Añade una entrada bajo models con provider openai, apiBase apuntando a la base URL de avots, tu clave av_mcp_ y el id del modelo.

3. Recarga y elige el modelo

Guarda, recarga Continue y elige el nuevo modelo en el desplegable del asistente.

~/.continue/config.yaml
models:
  - name: Claude Sonnet (avots)
    provider: openai
    model: anthropic/claude-sonnet-4.6
    apiBase: https://api.avots.ai/openai/v1
    apiKey: av_mcp_YOUR_KEY

provider debe ser openai (el adaptador genérico compatible con OpenAI), no anthropic, o Continue llegará a la API nativa de Anthropic. Mantén /v1 en apiBase. config.yaml reemplaza al antiguo config.json; si aparecen errores de streaming o de la Responses API, añade useResponsesApi: false.

Example request

curl
curl https://api.avots.ai/openai/v1/chat/completions \
  -H "Authorization: Bearer av_mcp_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-sonnet-4.6",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Model and MCP tools in one config

Continue keeps the chat provider and MCP servers in the same file, so you paste both at once and get Claude, GPT and Gemini plus the avots creative tools (image, video, audio, talking avatars) on one av_mcp_ key. You save it yourself, nothing is added automatically.

~/.continue/config.yaml, model + MCP tools
models:
  - name: Claude Sonnet (avots)
    provider: openai
    model: anthropic/claude-sonnet-4.6
    apiBase: https://api.avots.ai/openai/v1
    apiKey: av_mcp_YOUR_KEY

mcpServers:
  - name: avots
    type: streamable-http
    url: https://mcp.avots.ai/
    requestOptions:
      headers:
        Authorization: Bearer av_mcp_YOUR_KEY

MCP setup guide →

Models and prices

Set the model field to any id below, or a lazy name like claude / gpt / gemini that maps to a sensible default.

ModelBest for⚡ / 1M tokens (in / out)
openai/gpt-5.5-proMax intelligence, hardest tasks60 000 / 360 000
anthropic/claude-opus-5Top Claude, long reasoning10 000 / 50 000
anthropic/claude-sonnet-4.6Balanced (default)6 000 / 30 000
google/gemini-3.1-pro-previewFresh Gemini Pro4 000 / 24 000
google/gemini-2.5-proStable Gemini Pro2 500 / 20 000
anthropic/claude-haiku-4.5Fast Claude2 000 / 10 000
deepseek/deepseek-r1Cheap reasoning1 400 / 5 000
google/gemini-2.5-flashFast and cheap600 / 5 000
openai/gpt-5-miniCheap OpenAI500 / 4 000
openai/gpt-oss-120b:freeFree (OpenAI open model, needs a positive balance)Free

* Price in ⚡ per 1,000,000 tokens, input / output (1000⚡ ≈ $1). Free models need a positive balance. Full list via GET /openai/v1/models.

Continue.dev con Claude, GPT y Gemini

Generate an av_mcp_ key in Settings, paste three fields, and reach 40+ models on one balance. The same key works for MCP.

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FAQ

Preguntas

¿config.yaml o config.json?
config.yaml es el formato actual y tiene prioridad sobre cualquier config.json antiguo. Pon el modelo de avots en la lista models.
¿Por qué provider openai para Claude?
Porque avots es compatible con OpenAI. provider openai usa la ruta /chat/completions; provider anthropic se saltaría avots.
¿VS Code y JetBrains a la vez?
Sí. Continue comparte el mismo config.yaml entre ambos IDE.
¿Cómo se factura?
Por solicitud desde tu saldo de avots.
Does it support function calling and tools?
Yes. The endpoint forwards the standard OpenAI tools, tool_choice and parallel_tool_calls fields (and the legacy functions/function_call), in both streaming and non-streaming mode, so agent frameworks like LangChain, LlamaIndex, Langflow and n8n get real tool_calls back. Whether a given request uses tools depends on the model you pick: Claude, GPT and Gemini all support function calling.

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