by hiveflowai
Streamline business management processes with HiveFlow's workflow automation software. Trigger automated workflows and a
Connects AI assistants to HiveFlow's automation platform for managing and executing business workflows through conversation.
HiveFlow is a community-built MCP server published by hiveflowai that provides AI assistants with tools and capabilities via the Model Context Protocol. Streamline business management processes with HiveFlow's workflow automation software. Trigger automated workflows and a It is categorized under ai ml, developer tools.
You can install HiveFlow in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
HiveFlow is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
HiveFlow reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
HiveFlow has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
HiveFlow reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend HiveFlow for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We evaluated HiveFlow against two servers with overlapping tools; this profile had the clearer scope statement.
I recommend HiveFlow for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
HiveFlow is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We wired HiveFlow into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Strong directory entry: HiveFlow surfaces stars and publisher context so we could sanity-check maintenance before adopting.
HiveFlow is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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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 [email protected]
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: '[email protected]'}"
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-serverFor 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
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.