by hiveflowai
Bridges AI assistants such as Claude or Cursor with the HiveFlow automation platform, enabling flow creation, execution, and management via AI commands.
Provides a Model Context Protocol server that acts as a bridge between AI assistants and the HiveFlow automation platform, exposing flow‑management tools and resources to the assistant.
npm install -g @hiveflow/mcp-server
.cursor/mcp.json
):
{
"mcpServers": {
"hiveflow": {
"command": "npx",
"args": ["-y", "@hiveflow/mcp-server"],
"env": {
"HIVEFLOW_API_KEY": "your-api-key-here",
"HIVEFLOW_API_URL": "https://api.hiveflow.ai"
}
}
}
}
create_flow
, list_flows
, get_flow
, execute_flow
, pause_flow
, resume_flow
, get_flow_executions
.list_mcp_servers
, create_mcp_server
.hiveflow://flows
, hiveflow://executions
.DEBUG=hiveflow-mcp:*
.Q: "HIVEFLOW_API_KEY is required" error? A: Ensure the environment variable is set in the MCP configuration and the key is valid.
Q: Cannot connect to HiveFlow API?
A: Verify HIVEFLOW_API_URL
points to a running HiveFlow instance and there are no network/firewall restrictions.
Q: MCP server not found by the AI assistant? A: Restart the assistant, confirm the config file location, and ensure the package is installed globally.
Q: How to enable detailed logs?
A: Set DEBUG=hiveflow-mcp:*
in your environment before launching the server.
Official Model Context Protocol (MCP) server for HiveFlow. Connect your AI assistants (Claude, Cursor, etc.) directly to your HiveFlow automation platform.
npm install -g @hiveflow/mcp-server
Add to your MCP client configuration (e.g., .cursor/mcp.json
):
{
"mcpServers": {
"hiveflow": {
"command": "npx",
"args": ["-y", "@hiveflow/mcp-server"],
"env": {
"HIVEFLOW_API_KEY": "your-api-key-here",
"HIVEFLOW_API_URL": "https://api.hiveflow.ai"
}
}
}
}
{
"mcpServers": {
"hiveflow": {
"command": "npx",
"args": ["-y", "@hiveflow/mcp-server"],
"env": {
"HIVEFLOW_API_KEY": "your-api-key-here",
"HIVEFLOW_API_URL": "http://localhost:5000"
}
}
}
}
cd your-hiveflow-backend
node get-api-key.js your-email@example.com
Once configured, you'll have access to these tools in your AI assistant:
create_flow
- Create new automation flowslist_flows
- List all your flowsget_flow
- Get details of a specific flowexecute_flow
- Execute a flow with optional inputspause_flow
- Pause an active flowresume_flow
- Resume a paused flowget_flow_executions
- Get execution historylist_mcp_servers
- List configured MCP serverscreate_mcp_server
- Register new MCP servershiveflow://flows
- Access to all your flows datahiveflow://mcp-servers
- MCP servers configurationhiveflow://executions
- Flow execution historyAI: "Create a flow called 'Email Processor' that analyzes incoming emails"
AI: "Show me all my active flows"
AI: "Execute the flow with ID 'abc123' with input data {email: 'test@example.com'}"
AI: "What's the status of my Email Processor flow?"
HIVEFLOW_API_KEY
- Your HiveFlow API key (required)HIVEFLOW_API_URL
- Your HiveFlow instance URL (default: https://api.hiveflow.ai)HIVEFLOW_INSTANCE_ID
- Instance ID for multi-tenant setups (optional)hiveflow-mcp --api-key YOUR_KEY --api-url https://your-instance.com
This MCP server acts as a bridge between your AI assistant and HiveFlow:
AI Assistant (Claude/Cursor) ↔ MCP Server ↔ HiveFlow API
"HIVEFLOW_API_KEY is required"
"Cannot connect to HiveFlow API"
"MCP server not found"
npm list -g @hiveflow/mcp-server
For detailed logging, set the environment variable:
export DEBUG=hiveflow-mcp:*
We welcome contributions! Please see our Contributing Guide for details.
MIT License - see LICENSE file for details.
Made with ❤️ by the HiveFlow team
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{ "mcpServers": { "hiveflow": { "command": "npx", "args": [ "-y", "@hiveflow/mcp-server" ], "env": { "HIVEFLOW_API_KEY": "<YOUR_API_KEY>", "HIVEFLOW_API_URL": "https://api.hiveflow.ai" } } } }
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