openai-compatible-mcp 0.2.4

MCP server that bridges to any OpenAI-compatible chat API (DeepSeek, OpenAI, Azure, local llama.cpp, etc.).

openai-compatible-mcp

A Model Context Protocol (MCP) server that bridges to any OpenAI-compatible chat API — DeepSeek, OpenAI, Azure OpenAI, OpenRouter, Together, Groq, local llama.cpp, and friends.

Default provider: DeepSeek. Switch to any OpenAI-compatible endpoint with a single environment variable.

The server runs over stdio (the standard MCP transport) and exposes two tools that any MCP-compatible client can call:

• chat — send a chat completion, get the assistant's reply
• list_models — show the configured default model and friendly aliases

Features

• Zero third-party dependencies (Python 3.9+ stdlib only)
• Works with any OpenAI-compatible chat API
• Friendly model aliases (deepseek-v4-flash → deepseek-v4-flash, r1 → deepseek-reasoner, etc.)
• Optional reasoning content extraction (DeepSeek-R1 style)
• Built-in JSON-RPC 2.0 over stdio MCP transport
• Tiny: ~400 lines of code

Quick start

Option A: one-click wizard (recommended)

Double-click setup\install.bat (Windows) or run ./setup/install.sh (macOS / Linux). A browser opens with a guided wizard — pick your provider, paste your API key, check the MCP clients you want to configure, and click "Apply". The wizard:

1. Detects Python / pip / package status
2. Installs / upgrades the package from PyPI
3. Tests the connection to your provider
4. Writes the right config files for each MCP client (Claude Desktop, Cursor, Claude Code, Codex) without overwriting any other servers you've configured
5. Optionally sets up auto-start on login

See setup/README.md for details.

Option B: command line

1. Install

From source:

git clone https://github.com/xiaobaotalks/openai-compatible-mcp.git
cd openai-compatible-mcp
pip install -e .

Or run directly without installing:

PYTHONPATH=src python -m openai_compatible_mcp

2. Configure

Set your API key and (optionally) the base URL:

# DeepSeek (default)
export DEEPSEEK_API_KEY="sk-..."

# OpenAI
export OPENAI_API_KEY="sk-..."
export OPENAI_COMPATIBLE_MCP_BASE_URL="https://api.openai.com"

# Azure OpenAI
export OPENAI_COMPATIBLE_MCP_API_KEY="..."
export OPENAI_COMPATIBLE_MCP_BASE_URL="https://YOUR-RESOURCE.openai.azure.com/openai/deployments/YOUR-DEPLOYMENT"

# Local llama.cpp server
export OPENAI_COMPATIBLE_MCP_BASE_URL="http://127.0.0.1:8080"
export OPENAI_COMPATIBLE_MCP_DEFAULT_MODEL="llama-3.1-8b"

# Custom: anything speaking the OpenAI /v1/chat/completions protocol
export OPENAI_COMPATIBLE_MCP_API_KEY="..."
export OPENAI_COMPATIBLE_MCP_BASE_URL="https://my.example.com"
export OPENAI_COMPATIBLE_MCP_DEFAULT_MODEL="my-model"

Environment variable lookup order (first one set wins):

Setting	Variables tried (in order)
API key	OPENAI_COMPATIBLE_MCP_API_KEY → DEEPSEEK_API_KEY → OPENAI_API_KEY
Base URL	OPENAI_COMPATIBLE_MCP_BASE_URL → DEEPSEEK_API_BASE → OPENAI_BASE_URL
Default model	OPENAI_COMPATIBLE_MCP_DEFAULT_MODEL → DEEPSEEK_DEFAULT_MODEL

3. Wire it up to an MCP client

Claude Desktop

~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "openai-compatible": {
      "command": "python",
      "args": ["-m", "openai_compatible_mcp"],
      "env": {
        "DEEPSEEK_API_KEY": "sk-..."
      }
    }
  }
}

See examples/claude_desktop_config.json for a full sample.

Cursor

~/.cursor/mcp.json:

{
  "mcpServers": {
    "openai-compatible": {
      "command": "python",
      "args": ["-m", "openai_compatible_mcp"],
      "env": {
        "DEEPSEEK_API_KEY": "sk-..."
      }
    }
  }
}

Claude Code / other stdio clients

Same shape: launch python -m openai_compatible_mcp as a subprocess and read/write JSON-RPC over its stdin/stdout.

Tools

chat

Send a chat completion to the configured provider.

Field	Type	Required	Description
messages	array	yes	List of {role, content} messages (oldest first).
model	string	no	Model name or alias (e.g. deepseek-v4-flash, o1-mini).
temperature	number	no	0-2, lower = more deterministic.
max_tokens	integer	no	Maximum tokens to generate.
top_p	number	no	Nucleus sampling cutoff.
stop	string | array	no	Stop sequence(s).
system	string	no	System prompt (prepended to the conversation).
include_reasoning	boolean	no	Wrap reasoning content in <think>...</think>.

Example (from an MCP client):

{
  "method": "tools/call",
  "params": {
    "name": "chat",
    "arguments": {
      "messages": [
        {"role": "user", "content": "Write a haiku about Python."}
      ],
      "model": "deepseek-v4-flash",
      "temperature": 0.7
    }
  }
}

The tool returns text content with the assistant's reply plus a usage footer:

Whitespace glides through the code,
Indents bloom like spring leaves—
Bugs hide, then they are gone.

---
model: deepseek-v4-pro | prompt_tokens: 12 | completion_tokens: 28 | total_tokens: 40

list_models

Returns the default model and the alias table.

Built-in model aliases

You can edit src/openai_compatible_mcp/client.py to add or remove aliases for your provider. Defaults:

Alias	Resolves to
deepseek-v4-pro	deepseek-v4-pro
deepseek-v4-flash	deepseek-v4-flash
deepseek-v3	deepseek-v4-pro
deepseek-chat	deepseek-v4-pro
deepseek-reasoner	deepseek-reasoner
deepseek-r1	deepseek-reasoner
deepseek-coder	deepseek-v4-pro
gpt-4o	gpt-4o
gpt-4o-mini	gpt-4o-mini
o1	o1
o1-mini	o1-mini
o3-mini	o3-mini

Any model name not in the alias table is passed through to the provider unchanged, so the latest models work the moment a provider releases them.

Smoke test

Run the server and send a few raw JSON-RPC requests over stdio:

echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"smoke","version":"0"}}}' | python -m openai_compatible_mcp

Or use the included test client:

PYTHONPATH=src python tests/smoke_test.py

Development

# Create a venv
python -m venv .venv
.venv\Scripts\activate       # Windows
source .venv/bin/activate    # macOS / Linux

# Editable install
pip install -e ".[dev]"

# Run tests
PYTHONPATH=src python tests/smoke_test.py

License

MIT — see LICENSE.