Compatible with every major AI agent and IDE
Cancel run on LangGraph Cloud (Stateful AI Agents)
Interrupt and cancel an ongoing graph execution run
Create run on LangGraph Cloud (Stateful AI Agents)
Execute an assistant run on a specific thread with an input payload
Create thread on LangGraph Cloud (Stateful AI Agents)
Create a new LangGraph thread to hold conversational state
Get run on LangGraph Cloud (Stateful AI Agents)
Get complete details and status of a specific language graph run
Get thread state on LangGraph Cloud (Stateful AI Agents)
g., current messages array or structured outputs) generated by the LangGraph application. Retrieve the exact state graph and variables for a specific thread
List assistants on LangGraph Cloud (Stateful AI Agents)
List LangGraph deployed assistants (graph configurations)
List crons on LangGraph Cloud (Stateful AI Agents)
List active scheduled cron jobs automating agent runs
List runs on LangGraph Cloud (Stateful AI Agents)
List execution runs assigned to a specific thread
List threads on LangGraph Cloud (Stateful AI Agents)
List active LangGraph conversation threads
Update thread state on LangGraph Cloud (Stateful AI Agents)
Manually override or update a thread state graph
How Vinkius protects your data
Can I set different limits for each virtual assistant on my team?
Absolutely. You have full control in our command center. You can create an AI agent that only "reads" data so the support team can answer questions, and another superpowered agent that can "edit" and "create" information exclusively for your operations team. Each AI gets exactly the level of access you allow.
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
Can I audit what my AI agents are doing with this integration?
Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.
Can I manually approve an agent's step using this server?
Yes. Use the update_thread_state tool to perform manual node state overrides. This is the standard way to implement human-in-the-loop (HITL) patterns, allowing you to modify or approve graph variables directly mid-execution.
Triggering LangGraph Cloud (Stateful AI Agents) via Natural Language
Connect your AI agents and chatbots (Claude, ChatGPT, Cursor) with the LangGraph Cloud (Stateful AI Agents) MCP server to manage operations across the following domains.
Seamless ai agents Integration
Integrate ai agents features into your LLM framework using LangGraph Cloud (Stateful AI Agents). The MCP server ensures precise command execution across your superpower stack.
Claude Code Integration for stateful workflows
The LangGraph Cloud (Stateful AI Agents) connection gives ChatGPT direct access to stateful workflows tools. The integration handles the logic required for continuous superpower operations.
LangGraph Cloud (Stateful AI Agents). Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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