About agent-flow
agent-flow is an MCP server in the Agents category: let your AI agent maintain a living flowchart of your project - 14 MCP tools, auto-layout, zero-dependency HTML viewer. Stop reading 10,000-word status docs.
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Install
git clone https://github.com/farazpawle/agent-flowThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (4)
analyze_ideaContext-aware analysis of a planned idea.
Parameters not published.
plan_ideaDraft architectural concepts with optional **Focus Modes** (logic, vibe, security, etc.).
Parameters not published.
process_thoughtHigh-fidelity thinking tool with support for **Design Tokens**, axioms, and focus shifts.
Parameters not published.
reflect_ideaCritical self-reflection to harden specifications.
Parameters not published.
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README
AgentFlow 🚀
AgentFlow is a next-generation, premium agentic workflow system built on the Model Context Protocol (MCP). It transforms the way AI agents handle complex development tasks by bridging the gap between raw LLM reasoning and structured execution.
✨ The Vision: "Vibe Coding" Refined
AgentFlow is designed for the modern "Vibe Coder"—developers who prioritize high-level intent, rapid iteration, and stunning visual feedback.
- 🧠 Integrated Thought Chain: Native Support for complex multi-step reasoning (
plan→analyze→reflect). - 🎨 State-of-the-Art Dashboard: A premium Glassmorphism interface with Dynamic Background Gradients, fluid animations (15s ease infinite shift), and meticulous Light/Dark themes.
- 🎮 Real-Time Pulse: Live updates via SSE (Server-Sent Events). Watch your agent create, update, and reorder tasks in real-time.
- ⚛️ Dual Persistence: Robust storage support via SQLite for local portability or Supabase for enterprise-scale persistence.
- 📁 Intelligent Project Context: Auto-detects projects based on workspace paths or Git remote URLs, mapping local work to stable project identities.
🧭 The Core Workflow
AgentFlow promotes a high-integrity "Think-Then-Do" pipeline:
- 💡 Plan Idea: Draft initial concepts and design tokens.
- 🔍 Analyze: Deep dive into technical requirements and blockers.
- 🤔 Reflect: Self-critique the plan to catch edge cases before a single line of code is written.
- 🧩 Split: Automatically decompose the refined plan into a Topological DAG of tasks.
- ▶️ Execute: Move through tasks with built-in Verification Loops ensuring criteria are met.
⚙️ Technical Stack
- Backend: Node.js + TypeScript (High-performance ESM).
- MCP Implementation:
@modelcontextprotocol/sdkfor seamless tool-calling integration. - Persistence: SQLite (Local) / Supabase (Remote) via shared
DatabaseAdapter. - Dashboard: Vanilla JS + CSS (Custom Tokens) + D3.js for real-time dependency graph visualization.
- Communication: HTTP REST API + Server-Sent Events (SSE) for zero-latency UI updates.
🛠️ Advanced Toolset
🏗️ Reasoning Engine
| Tool | Description |
|---|---|
plan_idea |
Draft architectural concepts with optional Focus Modes (logic, vibe, security, etc.). |
analyze_idea |
Context-aware analysis of a planned idea. |
reflect_idea |
Critical self-reflection to harden specifications. |
process_thought |
High-fidelity thinking tool with support for Design Tokens, axioms, and focus shifts. |
📋 Task Orchestration
| Tool | Description |
|---|---|
split_tasks |
Converts specification into a task graph with Dependencies, Priority, and Category. |
reorder_tasks |
Legalizes manual reordering while strictly enforcing topological constraints. |
verify_task |
A mandatory validation step before task completion. |
get_project_context |
Workspace-aware project identification and switching. |
� Quick Start
🔽 Via Smithery (Recommended)
npx -y @smithery/cli install agent-flow --client claude
🔽 Manual Setup
git clone https://github.com/farazpawle/agent-flow.git
cd agent-flow
npm install
npm run build
🔌 Configuration
AgentFlow is optimized for Zero-Config starts, but uses a .env file for advanced customization.
1. Setup Environment
In your project root (where you run the agent), create a .env file:
# Example .env configuration
DATA_DIR="C:/MyProject/agent-flow-data" # REQUIRED: Absolute path
DB_TYPE="sqlite" # Options: sqlite, supabase
ENABLE_GUI="true" # Enable the visual dashboard
ENABLE_DETAILED_MODE="true" # Record conversation history
2. MCP Client Registration
Register the server in your MCP client (Cursor, Claude Desktop, etc.). Since AgentFlow auto-loads your .env, the configuration is minimal:
Cursor (~/.cursor/mcp.json):
{
"mcpServers": {
"agent-flow": {
"command": "npx",
"args": ["-y", "agent-flow"]
}
}
}
💡 Pro Tip: You can still override any
.envsetting by passing it directly in theenvblock of your client JSON if needed.
☁️ Supabase Cloud Setup
If you want to use Supabase instead of SQLite:
- Initialize Tables: Copy the content of
scripts/supabase-schema.sqland run it in your Supabase SQL Editor. - Verify Setup: Run
npm run supabase:checkto ensure all tables are correctly created and accessible. - Migrate local data: If you have local SQLite data, run
npm run supabase:migrateto push it to the cloud. - Update .env:
DB_TYPE="supabase" SUPABASE_URL="https://your-project.supabase.co" SUPABASE_SERVICE_KEY="your-service-role-key"
📄 License
MIT License. Created with ❤️ for the Vibe Coding community.
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.