Skip to main content

A simple client library to connect to any MCP server and interact with or without LLMs.

Project description

 _   _       _ __  __  ____ ____ 
| | | | ___ (_)  \/  |/ ___|  _ \
| | | |/ _ \| | |\/| | |   | |_) |
| |_| | | | | | |  | | |___|  __/ 
 \___/|_| |_|_|_|  |_|\____|_|    
  Universal MCP Client

UniMCP

A simple, Python-native client library to connect to any Model Context Protocol (MCP) server. UniMCP allows you to interact with tools seamlessly via native Python code, an interactive CLI, or an autonomous LLM agent.

Features

  • Multiple Transports: Connect to remote servers via SSE (http://...) or local executables via Stdio (server.py, npx ...).
  • Dynamic Tool Generation: Automatically converts MCP tools into native Python async functions with IDE support.
  • Interactive CLI Playground: Test and chat with your tools straight from the terminal.
  • LLM Integration: Built-in, provider-agnostic LLM wrapper (OpenAI, Groq, Ollama, etc.) to hook your MCP server tools directly into an autonomous agent.
  • Session Management: Automatically persist and resume multi-turn conversations with context awareness.

Installation

pip install unimcp

🚀 Interactive CLI

The CLI provides a quick way to chat with your MCP server without writing any code.

Quick Start

Run the chat command from your terminal:

unimcp-chat

Configuration

The CLI uses environment variables from your .env file by default. To make it work, add these to your .env:

  • MCP_SERVER: The endpoint of your server (e.g., http://localhost:8000/sse or reference/server.py).
  • LLM_API_KEY: Your LLM provider API key.
  • LLM_BASE_URL: The API base URL (e.g., for NVIDIA NIM or Gemini).
  • LLM_MODEL_NAME: The specific model you wish to use.

CLI Options

You can override environment variables using flags:

  • --url <url>: Override the server endpoint.
  • --api-key <key>: Override the API key.
  • --base-url <url>: Override the LLM base URL.
  • --model <name>: Override the model name.
  • --system-prompt "text": Set a custom system instruction.

Example:

unimcp-chat --url http://localhost:8000/sse --model meta/llama-3.1-70b --api-key sk-123...

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

unimcp-1.1.0.tar.gz (44.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

unimcp-1.1.0-py3-none-any.whl (23.3 kB view details)

Uploaded Python 3

File details

Details for the file unimcp-1.1.0.tar.gz.

File metadata

  • Download URL: unimcp-1.1.0.tar.gz
  • Upload date:
  • Size: 44.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for unimcp-1.1.0.tar.gz
Algorithm Hash digest
SHA256 9522fdf88575ad882d09312c2a064cb4ef6d64db339541a4bbd564626131667f
MD5 d1c66b2be3fc67d56fc4ee667b9a5b6f
BLAKE2b-256 7268796800e505de264dbcd7b6f229788b21b47d24fb06b16f51823e72dee623

See more details on using hashes here.

File details

Details for the file unimcp-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: unimcp-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 23.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for unimcp-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8f4eb51890e78908c99ed1a1ae6c8bdb7fa5743307ea8cae8c349ae536190d7f
MD5 fd0e9c2091e81919e5994176bca9dac7
BLAKE2b-256 e7ff151a6e8825edcd75ac3fce2cce1ab03314297f17b91dc531aa3326579956

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page