Hummingbot

io.github.hummingbotPublished by GitHub account hummingbotv0.1.0Updated Oct 24, 2026

MCP server exposing Hummingbot API for automated multi-exchange trading

VerifiedSTDIODesktop onlyFinanceBusiness & Commerce

Overview

AI-generated overview

Connects an assistant to a Hummingbot API server so it can manage crypto trading accounts, orders, positions, market data and bots across exchanges.

What you can do
  • Manage the API connection: view or update the Hummingbot API server URL and credentials, then reconnect.
  • Handle accounts and connectors, including setup of exchange connections.
  • Check portfolio balances and distribution.
  • Place and manage orders, and manage positions.
  • Read market data such as prices, order books, candles and funding rates.
  • Deploy and manage trading bots and configure their controllers.
When to use it
Useful when you already run a Hummingbot API server and want an assistant to inspect portfolios, market data and bots, or to place and manage orders and positions across multiple exchanges from a chat session.
Requirements
A local runtime: Python 3.11+ with uv, or the published Docker image. A running Hummingbot API server reachable at HUMMINGBOT_API_URL, plus valid HUMMINGBOT_USERNAME and HUMMINGBOT_PASSWORD. Optional tuning variables cover timeout, retries, retry delay and log level. On Docker for Mac/Windows the API URL must use host.docker.internal.
Before you install
The server holds Hummingbot API credentials (HUMMINGBOT_USERNAME, HUMMINGBOT_PASSWORD) and can change them through the configure_server tool; settings persist in a local server.yml file. Its tools place and manage real orders, positions and bots, so assistant actions can move funds and lose money. The README examples use default admin credentials, which should be replaced. Error messages echo the configured username and API URL.

Installation

In SourceWeft

  1. Open Hummingbot in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

MCP Hummingbot Server

An MCP (Model Context Protocol) server that enables Claude and Gemini CLI to interact with Hummingbot for automated cryptocurrency trading across multiple exchanges.

Installation & Configuration

Option 1: Using uv (Recommended for Development)

  1. Install uv (if not already installed):

    bash
    curl -LsSf https://astral.sh/uv/install.sh | sh
  2. Clone and install dependencies:

    bash
    git clone https://github.com/hummingbot/mcpcd mcpuv sync
  3. Create a .env file:

    bash
    cp .env.example .env
  4. Edit the .env file with your Hummingbot API credentials:

    env
    HUMMINGBOT_API_URL=http://localhost:8000HUMMINGBOT_USERNAME=adminHUMMINGBOT_PASSWORD=admin
  5. Configure in Claude Code or Gemini CLI:

    json
    {  "mcpServers": {    "hummingbot-mcp": {      "type": "stdio",      "command": "uv",      "args": [        "--directory",        "/path/to/mcp",        "run",        "main.py"      ]    }  }}

    Note: Make sure to replace /path/to/mcp with the actual path to your MCP directory.

Option 2: Using Docker (Recommended for Production)

  1. Create a .env file:

    bash
    touch .env
  2. Edit the .env file with your Hummingbot API credentials:

    env
    HUMMINGBOT_API_URL=http://localhost:8000HUMMINGBOT_USERNAME=adminHUMMINGBOT_PASSWORD=admin

    Important: When running the MCP server in Docker and connecting to a Hummingbot API on your host:

    • Linux: Use --network host (see below) to allow the container to access localhost:8000
    • Mac/Windows: Change HUMMINGBOT_API_URL to http://host.docker.internal:8000
  3. Pull the Docker image:

    bash
    docker pull hummingbot/hummingbot-mcp:latest
  4. Configure in Claude Code or Gemini CLI:

    For Linux (using --network host):

    json
    {  "mcpServers": {    "hummingbot-mcp": {      "type": "stdio",      "command": "docker",      "args": [        "run",        "--rm",        "-i",        "--network",        "host",        "--env-file",        "/path/to/mcp/.env",        "-v",        "$HOME/.hummingbot_mcp:/root/.hummingbot_mcp",        "hummingbot/hummingbot-mcp:latest"      ]    }  }}

    For Mac/Windows:

    json
    {  "mcpServers": {    "hummingbot-mcp": {      "type": "stdio",      "command": "docker",      "args": [        "run",        "--rm",        "-i",        "--env-file",        "/path/to/mcp/.env",        "-v",        "$HOME/.hummingbot_mcp:/root/.hummingbot_mcp",        "hummingbot/hummingbot-mcp:latest"      ]    }  }}

    (Remember to set HUMMINGBOT_API_URL=http://host.docker.internal:8000 in your .env file)

    Note: Make sure to replace /path/to/mcp with the actual path to your MCP directory.

Cloud Deployment with Docker Compose

For cloud deployment where both Hummingbot API and MCP server run on the same server:

  1. Create a .env file:

    bash
    touch .env
  2. Edit the .env file with your Hummingbot API credentials:

    env
    HUMMINGBOT_API_URL=http://localhost:8000HUMMINGBOT_USERNAME=adminHUMMINGBOT_PASSWORD=admin
  3. Create a docker-compose.yml:

    yaml
    services:  hummingbot-api:    container_name: hummingbot-api    image: hummingbot/hummingbot-api:latest    ports:      - "8000:8000"    volumes:      - ./bots:/hummingbot-api/bots      - /var/run/docker.sock:/var/run/docker.sock    environment:      - USERNAME=admin      - PASSWORD=admin      - BROKER_HOST=emqx      - DATABASE_URL=postgresql+asyncpg://hbot:hummingbot-api@postgres:5432/hummingbot_api    networks:      - emqx-bridge    depends_on:      - postgres
      mcp-server:    container_name: hummingbot-mcp    image: hummingbot/hummingbot-mcp:latest    stdin_open: true    tty: true    env_file:      - .env    environment:      - HUMMINGBOT_API_URL=http://hummingbot-api:8000    depends_on:      - hummingbot-api    networks:      - emqx-bridge
      # Include other services from hummingbot-api docker-compose.yml as needed  emqx:    container_name: hummingbot-broker    image: emqx:5    restart: unless-stopped    environment:      - EMQX_NAME=emqx      - EMQX_HOST=node1.emqx.local      - EMQX_CLUSTER__DISCOVERY_STRATEGY=static      - EMQX_CLUSTER__STATIC__SEEDS=[[email protected]]      - EMQX_LOADED_PLUGINS="emqx_recon,emqx_retainer,emqx_management,emqx_dashboard"    volumes:      - emqx-data:/opt/emqx/data      - emqx-log:/opt/emqx/log      - emqx-etc:/opt/emqx/etc    ports:      - "1883:1883"      - "8883:8883"      - "8083:8083"      - "8084:8084"      - "8081:8081"      - "18083:18083"      - "61613:61613"    networks:      emqx-bridge:        aliases:          - node1.emqx.local    healthcheck:      test: [ "CMD", "/opt/emqx/bin/emqx_ctl", "status" ]      interval: 5s      timeout: 25s      retries: 5
      postgres:    container_name: hummingbot-postgres    image: postgres:15    restart: unless-stopped    environment:      - POSTGRES_DB=hummingbot_api      - POSTGRES_USER=hbot      - POSTGRES_PASSWORD=hummingbot-api    volumes:      - postgres-data:/var/lib/postgresql/data    ports:      - "5432:5432"    networks:      - emqx-bridge    healthcheck:      test: ["CMD-SHELL", "pg_isready -U hbot -d hummingbot_api"]      interval: 10s      timeout: 5s      retries: 5
    networks:  emqx-bridge:    driver: bridge
    volumes:  emqx-data: { }  emqx-log: { }  emqx-etc: { }  postgres-data: { }
  4. Deploy:

    bash
    docker compose up -d
  5. Configure in Claude Code or Gemini CLI to connect to existing container:

    json
    {  "mcpServers": {    "hummingbot-mcp": {      "type": "stdio",      "command": "docker",      "args": [        "exec",        "-i",        "hummingbot-mcp",        "uv",        "run",        "main.py"      ]    }  }}

    Note: Replace hummingbot-mcp with your actual container name. You can find the container name by running:

    bash
    docker ps

Server Configuration

On first run, the server creates a default configuration from environment variables (or uses http://localhost:8000 with default credentials). Configuration is stored in ~/.hummingbot_mcp/server.yml.

Using the configure_server Tool

# Show the current server configurationconfigure_server()
# Update the host and portconfigure_server(host="192.168.1.100", port=8001)
# Update credentialsconfigure_server(username="admin", password="secure_password")
# Update everything at onceconfigure_server(    name="production",    host="prod-server",    port=8000,    username="admin",    password="secure_password")

Only the provided parameters are changed; omitted ones keep their current values. The client automatically reconnects after any update.

Environment Variables

The following environment variables can be set in your .env file for the MCP server:

VariableDefaultDescription
HUMMINGBOT_API_URLhttp://localhost:8000Initial default API server URL (used only on first run)
HUMMINGBOT_USERNAMEadminInitial username (used only on first run)
HUMMINGBOT_PASSWORDadminInitial password (used only on first run)
HUMMINGBOT_TIMEOUT30.0Connection timeout in seconds
HUMMINGBOT_MAX_RETRIES3Maximum number of retry attempts
HUMMINGBOT_RETRY_DELAY2.0Delay between retries in seconds
HUMMINGBOT_LOG_LEVELINFOLogging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)

Note: After initial setup, use the configure_server tool to update the server connection. Environment variables are only used to create the initial default configuration.

Requirements

  • Python 3.11+
  • Running Hummingbot API server
  • Valid Hummingbot API credentials

Available Tools

The MCP server provides tools for:

Server Management

  • configure_server: View or update the active Hummingbot API server connection
    • No parameters: show current server config
    • Any parameters: update and reconnect
    • Configuration persists in ~/.hummingbot_mcp/server.yml

Trading & Account Management

  • Account management and connector setup
  • Portfolio balances and distribution
  • Order placement and management
  • Position management
  • Market data (prices, order books, candles)
  • Funding rates
  • Bot deployment and management
  • Controller configuration

Development

To run the server in development mode:

bash
uv run main.py

To run tests:

bash
uv run pytest

Troubleshooting

The MCP server now provides comprehensive error messages to help diagnose connection and authentication issues:

Connection Errors

If you see error messages like:

  • ❌ Cannot reach Hummingbot API at <url> - The API server is not running or not accessible
  • ❌ Authentication failed when connecting to Hummingbot API - Incorrect username or password
  • ❌ Failed to connect to Hummingbot API - Generic connection failure

The error messages will include:

  • The exact URL being used
  • Your configured username (password is masked)
  • Specific suggestions on how to fix the issue
  • References to tools like configure_server

Common Solutions

  1. API Not Running:

    • Ensure your Hummingbot API server is running
    • Verify the API is accessible at the configured URL
  2. Wrong Credentials:

    • Use configure_server tool to update server credentials
    • Or check your .env file configuration
  3. Wrong URL:

    • Use configure_server tool to update the server URL
    • For Docker on Mac/Windows, use host.docker.internal instead of localhost
  4. Docker Network Issues:

    • On Linux, use --network host in your Docker configuration
    • On Mac/Windows, use host.docker.internal:8000 as the API URL

Error Prevention

The MCP server will:

  • Not retry on authentication failures (401 errors) - it will immediately tell you the credentials are wrong
  • Retry on connection failures with helpful messages about what might be wrong
  • Provide context about whether you're running in Docker and suggest appropriate fixes
  • Guide you to the right tools (configure_server) to fix issues

Source: README.md at commit 836f935

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.1.0LatestSep 16, 2026

Score

50% of the applicable checks met

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  • Reached in the last 30 days25 pts

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  • Auth declared10 pts

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  • Tools listed15 pts

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  • DescriptionRequired15 pts
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  • Documentation15 pts
  • License10 pts