Akash Network MCP. Manage decentralized GPU resources via natural language.
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Akash Network (Decentralized GPU & Cloud API) MCP Server lets you manage decentralized cloud resources directly. You can create new deployments using standard SDL manifests, bid on provider compute power, and monitor escrow balances.
Use your AI client to handle everything from resource provisioning for AI training to maintaining continuous service uptime.
What your AI agents can do
Add deposit
Adds specified USD funds to a deployment's escrow account.
Close deployment
Stops and removes an active deployment.
Create deployment
Creates a new deployment using an SDL manifest.
You create new deployments or update existing ones using standard SDL manifests.
You poll for bids from available providers and create leases to secure compute resources.
You monitor escrow balances and add USD deposits to keep services running.
You enable auto top-up settings to let your decentralized cluster scale automatically.
You retrieve detailed status information for deployments, leases, and network providers.
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Akash Network MCP Server: 13 Tools for Cloud Ops
These tools let you programmatically manage every step of your decentralized cloud lifecycle, from provisioning resources to monitoring escrow balances.
019e5cf9add deposit
Adds specified USD funds to a deployment's escrow account.
019e5cf9close deployment
Stops and removes an active deployment.
019e5cf9create deployment
Creates a new deployment using an SDL manifest.
019e5cf9create lease
Accepts provider bids and creates a compute lease.
019e5cf9enable auto top up
Turns on automatic funding to prevent deployment downtime.
019e5cf9get deployment
Retrieves full status details for a specific deployment.
019e5cf9get deployment settings
Gets the current auto top-up configuration for a deployment.
019e5cf9get provider
Retrieves specific details about a network provider.
019e5cf9list bids
Polls the network to retrieve current bids from providers for a deployment.
019e5cf9list deployments
Lists all currently active deployments on the network.
019e5cf9list providers
Lists all available compute providers across the Akash network.
019e5cf9update deployment
Modifies the configuration of an already active deployment.
019e5cf9update deployment settings
Changes operational settings for a deployment.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
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Make Your AI Do More
Start with Akash Network (Decentralized GPU & Cloud API), then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
This MCP Server connects your AI client directly to the Akash Network, letting you manage decentralized cloud resources. You're in charge of the entire lifecycle, from setting up a workload to shutting it down.
Provisioning Workloads
To start a new job, you'll use create_deployment with a standard SDL manifest. You can also change an existing deployment's config with update_deployment, or fully stop and remove it using close_deployment.
Securing Compute Time
Want to lock in some GPU time? You'll use list_bids to check current provider bids for a deployment, then you'll use create_lease to accept a bid and secure the compute resources. You can also check out who's out there by calling list_providers or get_provider for specific details.
Managing Funds
To keep your services running, you'll use add_deposit to put specified USD funds into a deployment's escrow account. You can monitor the current auto top-up status with get_deployment_settings, and check the full details of a deployment's setup using get_deployment.
Scaling Infrastructure
If you need your cluster to scale up automatically, you'll use enable_auto_top_up to turn on automatic funding, or update_deployment_settings to change the operational rules.
Inspecting State
Need to know what's going on? You'll use list_deployments to see every active job on the network, or get_deployment to pull the full status of a specific deployment. You'll also get all the current provider bids by running list_bids.
How Akash Network MCP Works
- 1 Subscribe to the Akash Network MCP Server and provide your API Key.
- 2 Use your AI client to issue a command (e.g., 'List all my deployments').
- 3 The server runs the tool, executes the API call, and returns the structured data (e.g., deployment list, bid data) to your client.
The bottom line is, your AI client talks to the server, and the server handles all the complex calls to the Akash API for you.
Who Is Akash Network MCP For?
AI researchers and DevOps engineers need this. If you run ML models or host complex services on decentralized cloud infrastructure, you need to manage the full lifecycle—from provisioning GPUs to funding the uptime. Stop juggling provider dashboards and start managing resources directly through your agent.
Spins up high-end GPU deployments for model training or inference without managing complex cloud APIs.
Uses familiar SDL manifests to manage and scale decentralized infrastructure directly from their IDE.
Builds and hosts dApps on a decentralized cloud, ensuring automated resource management and financial stability.
What Changes When You Connect
- Automated Uptime: Use
enable_auto_top_upto set up automated funding. Your deployment won't fail because you forgot to manually add funds. - Immediate Visibility: Quickly list all workloads with
list_deploymentsor check a specific status withget_deployment. You always know what's running. - Cost Control: Manage finances with
add_deposit. You can add funds to the escrow to extend runtime without manually dealing with the underlying API. - Resource Acquisition: Get compute power by running
list_bidsand then usingcreate_lease. You secure the resources you need at the best available price. - Deployment Flexibility: Use
create_deploymentorupdate_deploymentto spin up or modify workloads using standard SDL manifests, keeping your process consistent. - Network Overview: Check the landscape using
list_providersandget_providerto know which compute resources are available before you commit to a deployment.
Real-World Use Cases
Starting a new AI training run
An ML Engineer needs a high-end GPU cluster for a new model. They ask their agent to create_deployment using the necessary SDL manifest. The agent checks list_providers first to ensure suitable hardware exists, then runs list_bids to find the best price before finalizing the setup.
Maintaining a long-running service
The DevOps team runs a critical web app that needs constant uptime. Before the app fails, they ask the agent to get_deployment_settings and then run enable_auto_top_up. This ensures the service automatically gets funded and stays online.
Scaling up a service cluster
The Web3 developer sees traffic spikes and needs more nodes. They run update_deployment to increase the resource count and then use add_deposit to top up the escrow balance, ensuring the scaling happens without interruption.
Shutting down a test environment
A researcher finishes testing and needs to reclaim resources. They ask the agent to close_deployment for the specific DSEQ, immediately releasing the associated compute power and freeing up funds.
The Tradeoffs
Manually tracking deployment status
A user has to log into the Akash portal, find the specific deployment ID, and click 'View Status' across multiple tabs to confirm if the service is running or if the escrow is low.
→
Just ask your agent to get_deployment with the ID. It pulls all the status details in one shot. If you need to see everything, run list_deployments.
Forgetting to fund the service
The service runs fine for weeks, but the escrow balance drops below the required threshold, causing the deployment to fail unexpectedly because no one remembered to deposit funds.
→
Run enable_auto_top_up and monitor your settings with get_deployment_settings. This keeps the resource flow running automatically.
Updating the wrong configuration
A user changes a setting manually, but forgets to update the main deployment manifest, leading to a mismatch between the desired state and the live running service.
→
Always use update_deployment or update_deployment_settings. This keeps the manifest and the live resource state synchronized.
When It Fits, When It Doesn't
Use this if you need to manage the entire lifecycle of a high-performance, decentralized compute cluster, especially if you need GPU resources for ML or Web3. You must use this if you need to automate funding (add_deposit, enable_auto_top_up) or if you need to see the real-time bids for compute (list_bids).
Don't use this if you only need to check a single API endpoint's status. If you just need to list providers, a simpler infrastructure API might suffice. But if your goal is deployment management, this is the right toolset. Always verify the current state using get_deployment before attempting any changes with update_deployment.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Akash Network. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 13 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Managing decentralized cloud resources shouldn't require juggling 10 different dashboards.
Before this, if you needed to check on your cloud cluster, you had to log into the provider portal. Then you'd navigate to the deployment dashboard, find the specific workload ID, and manually check the status, the remaining budget, and the active lease status. It was a nightmare of clicks, tabs, and copy-pasting IDs.
Now, you just tell your agent, 'Show me the status of my main AI cluster.' The agent runs `get_deployment`, and you get all the details—status, resource count, and lease info—in one clean response. The whole thing is direct.
Akash Network (Decentralized GPU & Cloud API) MCP Server: Full Control
You no longer have to manually track bids or worry about running out of money. With the MCP Server, you can run `list_bids` to see current market rates, and then immediately use `create_lease` to lock in the resources you want. You can even run `add_deposit` to guarantee uptime.
The difference is that you manage the whole stack—from the resource acquisition to the funding—through simple commands. It's a unified control plane.
Common Questions About Akash Network MCP
How do I list all my active deployments using the list_deployments tool? +
Use list_deployments to get a summary of every active workload. This tool returns IDs and basic status info for all deployments running under your account.
Can I use add_deposit to fund a deployment? +
Yes, add_deposit adds specified USD funds to a deployment's escrow balance. This is how you extend the runtime of a service that needs more time.
What is the best way to get the current GPU bids using list_bids? +
list_bids polls the network and shows current bids from providers for a specific deployment. You use this data to decide if you should run create_lease.
How do I update a deployment's settings? +
Use update_deployment_settings if you need to change general operational settings. For changing the core workload definition, use update_deployment.
Do I need to worry about funding if I use enable_auto_top_up? +
No. enable_auto_top_up sets up automatic funding rules. As long as your overall account has funds, the deployment will scale and stay active without manual intervention.
How do I check the details of a specific deployment using the get_deployment tool? +
You call get_deployment and provide the deployment ID. This returns the full status, resource allocation, and current lease details for that specific workload.
What is the process for creating a new deployment using the create_deployment tool? +
You invoke create_deployment and pass the SDL manifest. This initiates the deployment process, locking in resources based on the provided configuration.
Where do I find information about available hardware using the list_providers tool? +
The list_providers tool retrieves network-wide provider details. This shows you which nodes are available to host your compute resources across the decentralized network.
How do I check for available provider bids after creating a deployment? +
Use the list_bids tool with your deployment's DSEQ. It typically takes 30-60 seconds for providers to submit bids for your workload.
Can I update a running deployment with a new SDL manifest? +
Yes! Use the update_deployment tool. Provide the existing DSEQ and your revised SDL string to apply changes to your active resources.
How do I prevent my deployment from closing due to insufficient funds? +
You can use add_deposit to manually add USD to the escrow, or use enable_auto_top_up to configure automatic funding based on your deployment's needs.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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