An astronaut overseeing a futuristic data hub
Download PDFMarkdown Version

Connect Task DAG Dependency Resolver to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Fix execution orders and find deadlocks in your task graphs.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Task DAG Dependency Resolver.

  1. 01

    Find isolated tasks

    This capability identifies tasks that are completely disconnected from the rest of your execution graph. It helps you spot nodes that won't run because they have no incoming or outgoing connections.

  2. 02

    Resolve execution order

    This capability calculates the valid sequence for your tasks. It also identifies specific groups of tasks that can be executed in parallel.

  3. 03

    Detect cycles

    This capability finds and describes the exact loop causing a deadlock in your pipeline. It points out the specific tasks creating the circular dependency.

Real work

What teams actually run

01

Agentic Orchestration

Organize task dependencies within frameworks like CrewAI or LangGraph.

02

Pipeline Debugging

Locate the specific loop causing a deadlock in a complex task sequence.

03

Workflow Optimization

Find tasks that can run in parallel to speed up your agent's work.

04

Graph Integrity Checks

Verify that every task in a large graph is actually reachable and connected.

One connector, every AI

Task DAG Dependency Resolver works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Task DAG Dependency Resolver to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

871ms average. Fast in production.

Task DAG Dependency Resolver is checked daily against the live service.

Daily averagePeak 1078ms
Oct 3Today
Fastest day
726ms
Slowest day
1078ms
14-day trend
Improving-12%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Task DAG Dependency Resolver, so you can see the experience inside your AI.

It does not authenticate your account with Task DAG Dependency Resolver. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Task DAG Dependency Resolver Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_PG7vL55vQOWAb30PXDjIN58o0NkWX6bQwzxPi4mp/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Task DAG Dependency Resolver capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "task-dag-dependency-resolver-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_PG7vL55vQOWAb30PXDjIN58o0NkWX6bQwzxPi4mp/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Task DAG Dependency Resolver in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Task DAG Dependency Resolver owners hand off.

This MCP is for developers building autonomous agent workflows that require strict task sequencing.

  • 01

    AI Engineers

    They hand off complex DAG structures to the agent to validate execution logic.

  • 02

    Workflow Developers

    They use it to debug broken pipelines in orchestration frameworks.

  • 03

    Data Engineers

    They use the graph math to organize complex data processing steps.

FAQ

Questions Task DAG Dependency Resolver owners ask.

  • 01

    What algorithm does this MCP use?

    It uses Kahn's algorithm to calculate valid execution sequences and parallel groups.

  • 02

    Can I use this with LangGraph?

    Yes, it is designed to manage complex task dependencies in frameworks like LangGraph and CrewAI.

  • 03

    How does it handle deadlocks?

    The detect_cycles capability finds and describes the exact loop causing the deadlock in your pipeline.

  • 04

    Does it work with Claude?

    Yes, it works with any MCP-compatible client including Claude, Cursor, and Windsurf.

  • 05

    How do I find tasks that aren't running?

    Use the find_isolated_tasks capability to identify nodes that are disconnected from the rest of the graph.

  • 06

    How do I find tasks that can run at the same time?

    You can use the resolve_execution_order capability, which returns parallelGroups containing sets of task IDs that share the same depth level in the dependency graph.

  • 07

    What happens if my task list has a circular dependency?

    If a cycle is detected, you can use detect_cycles to retrieve the exact cyclePath that forms the loop, allowing you to fix the deadlock.

  • 08

    Can I use this for LangGraph or CrewAI workflows?

    Yes, this server is specifically built to resolve execution orders for agentic pipelines like those used in LangGraph and CrewAI.

Explore

More in Productivity

Suggestions

Connect Task DAG Dependency Resolver to Claude, Cursor, ChatGPT & more