Theta MCP. Manage AI Deployments and Video Workflows.
Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Theta MCP Server lets your agent manage decentralized infrastructure directly. You can query blockchain data—check account balances with `rpc_get_account` or fetch block hashes using `rpc_get_block`.
It also handles EdgeCloud AI deployment (create, stop, list) and manages the full video pipeline: generating URLs via `video_create_upload_url`, transcoding assets, and orchestrating livestreams.
What your AI agents can do
Ai create deployment
Launches a new AI model or Jupyter Notebook environment on EdgeCloud.
Ai delete deployment
Terminates an existing AI deployment, cleaning up resources.
Ai list deployments
Retrieves a list of all current and past deployments associated with the project.
Create, list, start, or delete full-stack AI deployments on the EdgeCloud.
Get specific block details by hash or height, and check pending transactions in the mempool.
Lock/unlock local accounts and submit signed Theta/TFuel transactions synchronously or asynchronously.
Generate secure upload links, transcode raw videos, and manage live streaming objects.
Check available VM resource types or list all existing AI deployments in a project.
Ask AI about this MCP
Supported MCP Clients
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Theta MCP Server: 29 Tools for Web3 Infrastructure
These tools let your AI client perform everything from querying block hashes to managing GPU node lifecycles and transcribing media assets.
019e5d5fai create deployment
Launches a new AI model or Jupyter Notebook environment on EdgeCloud.
019e5d5fai delete deployment
Terminates an existing AI deployment, cleaning up resources.
019e5d5fai list deployments
Retrieves a list of all current and past deployments associated with the project.
019e5d5fai list standard templates
Shows the built-in, pre-configured AI templates available for use.
019e5d5fai list vm resources
Lists all machine types and GPU resources currently available on the EdgeCloud.
019e5d5fai start deployment
Restarts a GPU Node that has been stopped, bringing it back online for work.
019e5d5fai stop deployment
Shuts down a running GPU Node to save costs and free up resources.
019e5d5fcli list keys
Outputs all local account addresses managed by the Theta CLI integration.
019e5d5fcli lock key
Locks local accounts, preventing them from sending transactions until explicitly unlocked.
019e5d5fcli new key
Creates a new, encrypted account locally for secure key management.
019e5d5fcli send
Sends Theta or TFuel tokens from an active local account.
019e5d5fcli unlock key
Unlocks a specified local account, allowing it to send transactions again.
019e5d5frpc broadcast raw transaction
Submits a signed transaction data payload to the network immediately and waits for confirmation.
019e5d5frpc broadcast raw transaction async
Submits a signed transaction data payload asynchronously, allowing your agent to continue other work.
019e5d5frpc call smart contract
Simulates executing code within a smart contract environment locally before deploying it on-chain.
019e5d5frpc get account
Fetches detailed information and balance status for a specific Theta account address.
019e5d5frpc get block
Retrieves the complete details of a block using its unique hash identifier.
019e5d5frpc get block by height
Gets finalized details for any block at a specific, given height number on the chain.
019e5d5frpc get pending transactions
Checks the mempool to retrieve a list of transactions waiting to be confirmed by miners.
019e5d5frpc get transaction
Pulls specific transaction details using its unique hash, confirming what happened.
019e5d5frpc get version
Returns the current version number of the Theta blockchain software running on the network.
019e5d5fvideo create livestream
Sets up a new live stream object that tracks video content and metadata.
019e5d5fvideo create upload url
Generates a unique, temporary URL where external clients can upload large video files securely.
019e5d5fvideo get
Retrieves the metadata and status details for a specific video asset or stream.
019e5d5fvideo list
Lists all videos associated with your service account within the Theta media platform.
019e5d5fvideo list ingestors
Provides a list of available Edge Ingestor services that can handle video uploads.
019e5d5fvideo search
Searches the entire video library using specific metadata filters (e.g., date, tags).
019e5d5fvideo select ingestor
Assigns a specific Edge Ingestor service to manage and process an active stream.
019e5d5fvideo transcode
Processes raw video files, converting them into various formats (e.g., 1080p MP4) for distribution.
019e5d5fvideo unselect ingestor
Releases an assigned Edge Ingestor service from a stream, freeing up capacity.
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
- Publish to catalog or keep private
Make Your AI Do More
Start with Theta, 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
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- 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 server gives your agent direct command over decentralized infrastructure—everything from managing AI deployments on EdgeCloud to running full video pipelines and submitting blockchain transactions. You don't need a dedicated terminal; your agent handles it all.
AI Model Deployments:
Your agent can manage the entire lifecycle of AI models using tools like ai_list_standard_templates to see what built-in templates are ready for use, or ai_list_deployments to check every current and past deployment associated with your project. Need a new environment? You'll launch it by calling ai_create_deployment for a fresh AI model or Jupyter Notebook setup.
When you're done with the compute cycle, you can shut down resources using ai_stop_deployment to save cash, or delete the entire deployment via ai_delete_deployment. If a GPU Node gets stopped, you can bring it back online and ready for work by running ai_start_deployment; you'll also check available hardware types using ai_list_vm_resources.
Blockchain Operations:
Your agent lets you read the whole ledger. You can fetch detailed status and balances for any specific Theta account address with rpc_get_account. To track network movement, you can get finalized details for any block at a specific height using rpc_get_block_by_height, or pull complete data using a unique hash identifier via rpc_get_block.
For real-time monitoring, check the mempool contents to see all transactions waiting confirmation with rpc_get_pending_transactions, and drill down on specific events by getting transaction details with rpc_get_transaction using its unique hash. The network also gives you basic info like the current version number of the blockchain software running via rpc_get_version.
For sending money or data, your agent handles transactions securely. You'll list all local account addresses managed by the Theta CLI integration with cli_list_keys and create a new, encrypted key locally using cli_new_key. If you need to pause an account for safety, use cli_lock_key; when it’s clear everything is safe, run cli_unlock_key on that specific account.
You can send both Theta or TFuel tokens from an active local account with cli_send. For broadcasting raw transactions, you've got two options: submit a signed data payload immediately and wait for confirmation using rpc_broadcast_raw_transaction, or use rpc_broadcast_raw_transaction_async to send the data without forcing your agent to wait.
Key Management:
Beyond just sending tokens, you manage key security directly. You'll list all local account addresses with cli_list_keys; create a new encrypted account using cli_new_key; lock an existing account with cli_lock_key until it's safe to proceed; and unlock that account again when transactions are ready via cli_unlock_key.
Video Media Pipeline:
Your agent manages the entire media workflow. You can start by listing all videos tied to your service account using video_list, or search your entire library for specific assets based on metadata like date or tags, which you do with video_search. Before a big upload, generate a unique, temporary URL using video_create_upload_url; this is where external clients can securely drop large video files.
To process raw media, call video_transcode to convert files into multiple formats—say, 1080p MP4—for distribution. For live content, you'll first set up a new stream object using video_create_livestream, then assign an Edge Ingestor service using video_select_ingestor; remember to release that capacity later with video_unselect_ingestor. You can retrieve the metadata and status for any video asset or stream by running video_get, while checking available processing services with video_list_ingestors.
How Theta MCP Works
- 1 First, subscribe to the Theta server and give your agent the necessary credentials (RPC URL, EdgeCloud/Video API keys).
- 2 Then, tell your AI client what you need—for example: 'List all available VM resources for a new deployment.'
- 3 The agent executes the relevant tool (
ai_list_vm_resources), gets the data back, and reports it to you in plain English.
The bottom line is that your AI client uses these tools as functions it can call directly, letting you interact with complex systems like blockchain networks without writing boilerplate code.
Who Is Theta MCP For?
This is for the Web3 developer who needs to integrate core infrastructure tasks—like checking block hashes or sending tokens—into an application workflow. It's also for AI engineers scaling models on decentralized hardware, and content platform ops staff managing high-volume video ingestion.
You use rpc_get_block to verify transaction history or run smart contract simulations using rpc_call_smart_contract before writing final code.
You automate the deployment cycle. You check available resources with ai_list_vm_resources, then use ai_create_deployment to spin up a new model instance on EdgeCloud.
You manage video pipelines. When a client uploads footage, you automatically call video_create_upload_url, then trigger video_transcode and finally create the livestream object via video_create_livestream.
What Changes When You Connect
- Blockchain queries are instant. Instead of opening a separate RPC client, you use
rpc_get_blockorrpc_get_pending_transactionsdirectly in conversation to get real-time network status. - AI resource scaling is controlled via code. You can list templates with
ai_list_standard_templatesand then immediately launch a new environment usingai_create_deployment, all without leaving your agent's chat interface. - Video workflows become fully automated. When content arrives, the agent uses
video_create_upload_urlfor ingestion, followed byvideo_transcodeto get it ready for any platform. - Key management is secure and simple. You can list local keys with
cli_list_keysand usecli_unlock_keywhen you're ready to execute a financial transaction viacli_send. - Node state changes are direct commands. Need to pause costs? Use
ai_stop_deployment. Need it back? Callai_start_deployment. It’s simple, immediate control over your GPU resources.
Real-World Use Cases
Checking a Smart Contract Before Deployment
A dev finds an old contract address. Instead of guessing if the code is valid or if the gas limits are right, they tell their agent to run rpc_call_smart_contract with sample inputs. The agent simulates the execution locally, giving them immediate feedback on expected state changes before they commit to a live deployment.
Handling Live Video Ingestion
A content team is going live. They don't want manual steps. Their agent first calls video_create_upload_url for the raw stream, then uses video_select_ingestor to assign a worker service, and finally monitors status with video_get. The entire process runs without human intervention.
Monitoring Network Health Post-Incident
After an outage, the ops engineer needs to know what's stuck. They ask their agent for a list of pending transactions (rpc_get_pending_transactions) and then cross-reference those hashes by calling rpc_get_transaction until they find the missing data point.
Quickly Scaling AI Testing
A team needs to test a new model on high-end hardware. The agent first checks capacity using ai_list_vm_resources. Once confirmed, it runs ai_create_deployment for the required GPU size, then waits until the node is ready to start testing.
The Tradeoffs
Treating RPC calls like a database lookup
A user tries to 'get all transactions' by just calling rpc_get_transaction without parameters, assuming the tool knows what they mean. This fails because it requires a specific transaction hash.
→
To find recent activity, start by listing pending items using rpc_get_pending_transactions. Then, pick a hash from that list and call rpc_get_transaction(hash) to get the full details you need.
Forgetting key state management
A user tries to send tokens (cli_send) but hasn't unlocked the account first, resulting in an 'Account Locked' error and forcing them to start over.
→
Always check the status. If you suspect a lock, run cli_list_keys first. Then use cli_unlock_key(address) before attempting any transfer with cli_send.
Assuming deployment status is automatic
A user calls ai_create_deployment and immediately asks for the model output, but the node hasn't finished spinning up or allocating resources yet. The agent gives an error because the resource isn't ready.
→
After running ai_create_deployment, always follow up with ai_list_deployments to verify its status before sending it a command like 'run model inference'.
When It Fits, When It Doesn't
Use this Theta MCP Server if your process involves coordinating three distinct, high-complexity domains: decentralized finance/blockchain (RPC/CLI), cloud infrastructure management (AI Deployment), and media processing (Video). You need the agent to switch between these protocols fluidly. Don't use it if you only need one function—for example, if all you want is basic video searching, a dedicated media API tool will be simpler. If your goal is purely blockchain analysis without needing deployment orchestration, stick to pure RPC clients. This server handles cross-domain state changes and resource allocation.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Theta. 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 30 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Managing decentralized resources shouldn't require jumping between five different dashboards.
Right now, managing infrastructure means logging into a blockchain explorer for transaction history, then switching tabs to the cloud console to check GPU availability, and finally opening a separate media platform dashboard just to initiate transcoding. You spend half your time copying hashes and juggling credentials.
With this MCP server, you tell your agent, 'Check block 25000000 and if it's stable, deploy the new model.' The agent runs `rpc_get_block`, checks its status, then executes `ai_create_deployment`—all in one chat thread. It handles the handoffs.
Theta MCP Server: Orchestrate video and AI deployments from your prompt.
Manually handling a large asset means getting an upload URL, uploading the file via external tools, then manually triggering transcoding with specific parameters. If you mess up any step, the whole pipeline stalls.
Now, you simply ask your agent to 'Prep this video for our stream.' It automatically calls `video_create_upload_url`, waits for the data, runs `video_transcode` into required formats, and sets up the live feed via `video_create_livestream`. Done.
Common Questions About Theta MCP
How do I check the current network health using rpc_get_version? +
You run rpc_get_version to get the exact software version. This is useful for ensuring your client tools are compatible with what's running on the Theta blockchain.
What’s the difference between cli_send and rpc_broadcast_raw_transaction? +
cli_send handles the full process: it checks if your key is unlocked (cli_unlock_key) and then sends the tokens for you. rpc_broadcast_raw_transaction requires you to manually prepare a signed transaction payload.
How can I list available GPU resources with ai_list_vm_resources? +
Just prompt your agent to 'List VM resources.' The tool runs ai_list_vm_resources and returns specific hardware details, like the NVIDIA T4 type and available RAM/vCPU counts.
Can I search videos using video_search? +
Yes. You pass metadata filters—like a date range or a specific tag—to video_search. It finds matching assets across your entire service account's library instantly.
How do I manage key security after running cli_new_key? +
The system generates a new encrypted account and returns your private seed phrase. You must copy this phrase immediately and store it offline in a secure location. Never share or input this phrase into an online tool.
What is the proper sequence when I use video_create_upload_url followed by video_transcode? +
First, you generate the upload URL and push your raw asset to that endpoint. Once the ingestion confirms receipt, you call video_transcode with the resulting video ID. Transcoding then processes the file into multiple formats.
If I run ai_stop_deployment on a node that is already stopped, will it cause an error? +
No. The tool checks the current state first and simply confirms the deployment is inactive. You can safely use ai_stop_deployment regardless of the node's current status to ensure the command executes cleanly.
How do I check if a signed transaction is pending confirmation using rpc_get_pending_transactions? +
This tool returns a list of all transactions currently in the mempool. You can filter this data by your specific account address or transaction hash to see if it's waiting for block inclusion.
How can I check the balance and sequence of a specific Theta wallet? +
Use the rpc_get_account tool by providing the wallet address (0x...). The agent will return the coin balances and the current sequence number for that account.
Can I manage AI model deployments on Theta EdgeCloud? +
Yes. You can use ai_list_deployments to see active ones, and ai_create_deployment or ai_stop_deployment to control your AI infrastructure resources.
How do I search for existing video assets in my Theta library? +
Simply use the video_search tool. You can provide a query string to filter through your uploaded and transcoded video content.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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