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flowzap-xyz/flowzap-mcp

by Various

MCP server for FlowZap - Create workflow diagrams via AI assistants

F

MCP

flowzap-xyz/flowzap-mcp

Added 1 June 2026

Overview

FlowZap MCP is a Model Context Protocol server that lets AI assistants generate workflow diagrams. It translates natural language requests into structured diagram definitions, enabling developers to create flowcharts through chat interfaces.

Best for

Best for
Developers who want to quickly generate workflow diagrams using AI assistants

Use cases

  • Generate workflow diagrams from conversational prompts
  • Integrate diagram creation into AI-assisted development workflows
  • Automate documentation of process flows via AI assistants

How to use

Install

npx skills add flowzap-xyz/flowzap-mcp

Tools exposed

  • flowzap_validate
  • flowzap_create_playground
  • flowzap_get_syntax
  • flowzap_export_graph
  • flowzap_artifact_to_diagram
  • flowzap_diff
  • flowzap_apply_change
  • flowzap_compliance_check

Tested with

Claude Desktop, Claude Code, Cursor, Windsurf, Cline, Continue, VS Code, ChatGPT

Example client config

{\n  "mcpServers": {\n    "flowzap": {\n      "command": "npx",\n      "args": ["-y", "flowzap-mcp"]\n    }\n  }\n}

Notes

FlowZap MCP is a Model Context Protocol server that lets AI assistants generate workflow diagrams. It translates natural language requests into structured diagram definitions, enabling developers to create flowcharts through chat interfaces.

4 stars on GitHub. Last updated 2026-05-26. Licensed MIT.

Use cases

  • Generate workflow diagrams from conversational prompts
  • Integrate diagram creation into AI-assisted development workflows
  • Automate documentation of process flows via AI assistants

Pros

  • Low friction: no manual diagramming tools needed
  • Leverages existing MCP ecosystem for AI integration
  • TypeScript codebase is approachable for most developers

Cons

  • Limited to diagram generation; no editing or collaboration features
  • Dependent on MCP-compatible AI assistants
  • Small community and limited documentation due to early stage

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Low friction: no manual diagramming tools needed
  • Leverages existing MCP ecosystem for AI integration
  • TypeScript codebase is approachable for most developers

Cons

  • Limited to diagram generation; no editing or collaboration features
  • Dependent on MCP-compatible AI assistants
  • Small community and limited documentation due to early stage
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