Power your agent
การติดตั้งจากผู้เผยแพร่ ไม่ใช่เอนด์พอยต์ของ PlugMCP
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รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดจากผู้เผยแพร่
Airflow runs DAGs but requires Kubernetes. Temporal does durable execution but needs a server. GitHub Actions does CI but can't branch dynamically. Zapier connects triggers but can't roll back. Every tool requires infrastructure, and none is AI-native.
Universal orchestration engine for AI agents — workflows, pipelines, state machines, batch processing. 24 inventions, 124 MCP tools, .awf format. Rust core + MCP server.
The current fixes don't work. YAML pipelines are rigid -- you can't add a step at runtime. Cron schedulers don't know about holidays or service health. Retry logic is one-size-fits-all. Approval gates are yes/no checkboxes. And no orchestration tool lets your AI agent create, modify, and reason about the workflow itself.
AgenticWorkflow orchestrates every coordination pattern in a single engine. DAGs, state machines, batch processing, stream processing, fan-out/fan-in -- all through 124 MCP tools. Not "configure a YAML file." Your agent thinks about workflows -- plans them, validates them, executes them, retries intelligently, rolls back on failure, and learns from every execution.
.awf binary file. Zero infrastructure. Works offline.use agentic_workflow::{Workflow, StepNode, StepType, Edge, EdgeType};
use agentic_workflow::engine::DagEngine;
let mut engine = DagEngine::new();
// Define a deployment pipeline
let mut wf = Workflow::new("deploy-pipeline", "Build, test, approve, deploy");
let build = StepNode::new("Build", StepType::Command {
command: "cargo".into(), args: vec!["build".into(), "--release".into()],
});
let test = StepNode::new("Test", StepType::Command {
command: "cargo".into(), args: vec!["test".into()],
});
let approve = StepNode::new("Approve", StepType::ApprovalGate {
approvers: vec!["[email protected]".into()], timeout_ms: Some(3600_000),
});
let deploy = StepNode::new("Deploy", StepType::McpTool {
sister: "connect".into(), tool: "deploy".into(),
params: serde_json::json!({"target": "production"}),
});
let (bid, tid, aid, did) = (build.id.clone(), test.id.clone(), approve.id.clone(), deploy.id.clone());
wf.add_step(build); wf.add_step(test); wf.add_step(approve); wf.add_step(deploy);
wf.add_edge(Edge { from: bid, to: tid.clone(), edge_type: EdgeType::Sequence });
wf.add_edge(Edge { from: tid, to: aid.clone(), edge_type: EdgeType::Sequence });
wf.add_edge(Edge { from: aid, to: did, edge_type: EdgeType::Sequence });
// Validate and execute
engine.register_workflow(wf).unwrap();
Six categories. Twenty-four capabilities. Every orchestration pattern that exists or will exist.
Rust core. In-memory engines. Real numbers from stress tests:
All stress tests measured on Apple ARM64, Rust 1.82, release profile. Every benchmark has a corresponding named test (
stress_dag_1000_steps_linear_chain,stress_batch_10k_items, etc.).
One-liner (desktop profile, backwards-compatible):
curl -fsSL https://agentralabs.tech/install/workflow | bash
Downloads pre-built awf and agentic-workflow-mcp binaries to ~/.local/bin/ and merges the MCP server into your Claude Desktop and Claude Code configs. If release artifacts are not available, the installer automatically falls back to cargo install --git source install.
Environment profiles (one command per environment):
# Desktop MCP clients (auto-merge Claude Desktop + Claude Code when detected)
curl -fsSL https://agentralabs.tech/install/workflow/desktop | bash
# Terminal-only (no desktop config writes)
curl -fsSL https://agentralabs.tech/install/workflow/terminal | bash
# Remote/server hosts (no desktop config writes)
curl -fsSL https://agentralabs.tech/install/workflow/server | bash
Any MCP-compatible client gets instant access to universal workflow orchestration. The agentic-workflow-mcp crate exposes the full engine over the Model Context Protocol (JSON-RPC 2.0 over stdio).
cargo install agentic-workflow-mcp
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"agentic-workflow": {
"command": "agentic-workflow-mcp",
"args": ["serve"]
}
}
}
Add to .vscode/settings.json:
{
"mcp.servers": {
"agentic-workflow": {
"command": "agentic-workflow-mcp",
"args": ["serve"]
}
}
}
Once connected, the LLM can create workflows, validate DAGs, execute pipelines, manage state machines, approve deployments, query audit trails, and predict execution outcomes -- all backed by the same .awf binary file.
→ workflow_create { name: "daily-report", description: "Generate metrics" }
← { workflow_id: "wf-a1b2c3", steps: 0, status: "created" }
→ workflow_step_add { workflow_id: "wf-a1b2c3", name: "Query DB", type: "mcp_tool" }
← { step_id: "s-d4e5f6", position: 1 }
→ workflow_validate { workflow_id: "wf-a1b2c3" }
← { valid: true, steps: 3, edges: 2, warnings: [] }
→ workflow_run { workflow_id: "wf-a1b2c3" }
← { execution_id: "ex-g7h8i9", status: "running" }
→ workflow_progress { execution_id: "ex-g7h8i9" }
← { completed: 2, total: 3, percent: 66.7, eta_ms: 45000 }
→ workflow_fsm_create { name: "order", initial: "Created", states: [...], transitions: [...] }
← { fsm_id: "fsm-j0k1l2" }
→ workflow_fsm_transition { fsm_id: "fsm-j0k1l2", event: "pay" }
← { from: "Created", to: "Paid", timestamp: "..." }
→ workflow_fsm_transition { fsm_id: "fsm-j0k1l2", event: "ship" }
← { from: "Paid", to: "Shipped" }
AgenticWorkflow orchestrates every coordination pattern through six subsystems:
+-------------------------------------+
| HEADER 16 bytes | AWFL magic . version . counts
+-------------------------------------+
| WORKFLOW REGISTRY | All workflow definitions
| (type u8 | length u32 | JSON | BLAKE3)
+-------------------------------------+
| TEMPLATE LIBRARY | Stored templates
+-------------------------------------+
| EXECUTION HISTORY | Past execution records
+-------------------------------------+
| SCHEDULE TABLE | Active schedules
+-------------------------------------+
| STATE MACHINE TABLE | FSM definitions + current states
+-------------------------------------+
| TRIGGER INDEX | Active triggers
+-------------------------------------+
| AUDIT LOG | Structured audit events
+-------------------------------------+
| IDEMPOTENCY CACHE | Deduplication keys
+-------------------------------------+
| VARIABLE STORE | Scoped variables
+-------------------------------------+
Each section independently BLAKE3-checksummed. Corruption in one section doesn't affect others. LZ4 compression available.
One research paper:
agentic-workflow/
├── Cargo.toml # Workspace root
├── crates/
│ ├── agentic-workflow/ # Core library (types, engines, resilience, governance, intelligence)
│ ├── agentic-workflow-mcp/ # MCP server (124 tools, stdio transport)
│ ├── agentic-workflow-cli/ # CLI binary (awf)
│ └── agentic-workflow-ffi/ # FFI bindings (C/Python/WASM)
├── assets/ # Agentra design system SVGs
├── paper/ # Research papers (I: Orchestration Engine)
├── scripts/ # Install + guardrail scripts
├── docs/ # Quickstart, API ref, concepts, benchmarks
└── .github/workflows/ # CI/CD pipelines
# All workspace tests (unit + integration)
cargo test --workspace
# Stress tests only
cargo test -p agentic-workflow stress
# Single phase
cargo test -p agentic-workflow --test phase7_stress
.awf file holds everything.Your agent's orchestration state. One file. Zero infrastructure.
"Orchestration tools shouldn't require more infrastructure than the workflows they orchestrate."
AgenticWorkflow stores everything in a single binary file. No Kubernetes. No managed services. No YAML. Your agent thinks in workflows -- let it.
Universal orchestration engine for AI agents — workflows, pipelines, state machines, batch processing. 24 inventions, 124 MCP tools, .awf format. Rust core + MCP server.
เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
Agentic Workflow ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-10-27 Universal orchestration engine for AI agents — workflows, pipelines, state machines, batch processing. 24 inventions, 124 MCP tools, .awf format. Rust core + MCP server.