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Server Gpt Chat

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MCP server for OpenAI ChatGPT API. Enables chat completions, vision analysis, embeddings, and model listing through natural language.

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Описание

MCP server for OpenAI ChatGPT API. Enables chat completions, vision analysis, embeddings, and model listing through natural language.

README

An MCP (Model Context Protocol) server for the OpenAI ChatGPT API. Built in Rust, exposes chat completions, vision, embeddings, and model listing as MCP tools.

Communicates via stdio using JSON-RPC 2.0, like all MCP servers.

Tools

Tool Description
chat Send a chat completion request to ChatGPT with optional multi-turn history, system prompt, structured output (JSON schema), and model selection
chat_with_vision Analyse an image with ChatGPT's vision capabilities given an image URL and text prompt
embedding Generate text embeddings using OpenAI's embedding model
list_models List all available OpenAI models and their IDs

chat

Send a chat completion request. Supports multi-turn conversations via a JSON message history array, system prompts, structured output via JSON schema, temperature control, and model selection.

Parameters:

Name Type Required Description
prompt string yes The user message to send
model string no Model to use (default: gpt-4o)
system_prompt string no System prompt to set context
messages string no Full conversation history as JSON array of {role, content} objects
temperature float no Sampling temperature (0.0 - 2.0)
max_tokens integer no Maximum tokens to generate
response_schema string no JSON schema string to enforce structured output

chat_with_vision

Analyse an image using ChatGPT's vision capabilities.

Parameters:

Name Type Required Description
prompt string yes Text prompt describing what to analyse
image_url string yes URL of the image (must be http:// or https://)
model string no Model to use (default: gpt-4o)
detail string no Image detail level: low or high (default: high)
temperature float no Sampling temperature (0.0 - 2.0)
max_tokens integer no Maximum tokens to generate

embedding

Generate text embeddings.

Parameters:

Name Type Required Description
input string yes Text to embed as JSON: a single string or array of strings
model string no Embedding model to use (default: text-embedding-3-small)

list_models

List all available OpenAI models. No parameters.

Prerequisites

Setup

Create the config file:

mkdir -p ~/.config/mcp-server-gpt-chat

Create ~/.config/mcp-server-gpt-chat/config.toml:

api_key = "sk-..."

Build

cargo build --release

This produces target/release/gpt-chat.

For development:

cargo build              # debug build
cargo run                # run in dev mode
RUST_LOG=debug cargo run # run with debug logging

MCP Configuration

Add to your Claude Desktop config (~/.config/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "gpt-chat": {
      "command": "/path/to/gpt-chat"
    }
  }
}

Project Structure

src/
  main.rs    - entry point, config loading, stdio transport setup
  server.rs  - MCP tool definitions (chat, chat_with_vision, embedding, list_models)
  api.rs     - OpenAI HTTP client, request/response types, response formatters
  params.rs  - tool parameter types with serde and JSON Schema derives
  config.rs  - TOML config loading

License

MIT

from github.com/codeChap/mcp-server-gpt-chat

Установка Server Gpt Chat

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/codeChap/mcp-server-gpt-chat

FAQ

Server Gpt Chat MCP бесплатный?

Да, Server Gpt Chat MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Server Gpt Chat?

Нет, Server Gpt Chat работает без API-ключей и переменных окружения.

Server Gpt Chat — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Server Gpt Chat в Claude Desktop, Claude Code или Cursor?

Открой Server Gpt Chat на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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