Cloudera AI Agent Studio MCP Server
LocalAbout Cloudera AI Agent Studio MCP Server
Cloudera AI Agent Studio MCP Server connects MCP-aware clients to Agent Studio so teams can inspect and assemble workflows. Its tools cover workflow metadata, conversational setup, and agent management.
Key features
- 01List workflow IDs and names
- 02Retrieve workflow metadata
- 03Create blank workflows
- 04Enable conversational tasks
- 05Add manager and specialist agents
Use cases
- 01Browse existing Agent Studio workflows
- 02Inspect tasks and process settings
- 03Scaffold a new workflow
- 04Build delegated agent workflows
MCP support
Exposes Cloudera AI Agent Studio workflow operations as tools for MCP clients, including listing, inspecting, creating, and modifying workflows.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMECloudera AI Agent Studio MCP Server
Agent Studio MCP Server is a lightweight Model Context Protocol (MCP) bridge that exposes your Agent Studio instance as a set of callable tools. It lets Claude (or any other MCP-aware client) list, inspect, and build Agent Studio workflows on the fly.
✨ What it can do
| Tool | Description | Typical Usage |
|---|---|---|
list_current_workflows() | Returns every workflow’s ID and name | Populate a UI drop-down of existing projects |
get_workflow_information(id) | Fetch full JSON metadata for one workflow | Inspect tasks, agents, and process settings |
create_workflow(name, description) | Spin up a brand-new blank workflow | Automate project scaffolding |
make_workflow_conversational(workflow_id) | Adds a Conversational Task and flips is_conversational to true | Turn a static workflow into a chat-first experience |
add_manager_agent_to_workflow(workflow_id, …) | Creates a manager agent and wires it in as the workflow’s supervisor | Hierarchical / delegated workflows |
add_agent_to_workflow(workflow_id, …) | Adds any number of additional agents to a workflow | Expand the crew with domain specialists |
🖥 Integrating with Claude Desktop
Add the following block to your claude_desktop_config.json:
{
"mcpServers": {
"agent-studio": {
"command": "uv",
"args": [
"--directory",
"/path/to/cloudera-ai-agent-studio-mcp",
"run",
"serve.py"
],
"env": {
"CDSW_APIV2_KEY": "YOUR-TOKEN-HERE",
"AGENT_STUDIO_DOMAIN": "https://your-studio.CDSW_DOMAIN.cldr.work"
}
}
}
}
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.