# Cloudera AI Agent Studio

> Use this tool when you need to automate the creation and management of AI workflows and agents in Cloudera environments. It solves problems of complex backend interactions and API navigation, enabling developers to programmatically create and configure workflows, add agents, and enable conversational capabilities. The tool takes environment-configured credentials as input and provides outputs such as listed, created, and configured workflows, making it ideal for use cases involving multi-agent systems and hierarchical management structures.

Canonical page: https://skillsregistry.net/skills/jasonmeverett-cloudera-ai-agent-studio  
JSON: https://api.skillsregistry.net/v1/skills/jasonmeverett-cloudera-ai-agent-studio

## Description

Cloudera AI Agent Studio MCP Server provides a bridge between AI assistants and Cloudera's Agent Studio platform, enabling programmatic creation and management of AI workflows and agents. Built with Python using the FastMCP framework, it exposes tools for listing, creating, and configuring workflows, adding manager and specialized agents to workflows, and enabling conversational capabilities. The server communicates with the Agent Studio API using environment-configured credentials, handling the complex backend interactions required to set up multi-agent systems with hierarchical management structures. It's particularly valuable for developers who want to automate the creation of sophisticated agent-based workflows in Cloudera environments without navigating the underlying API complexity.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/jasonmeverett-cloudera-ai-agent-studio)
- **Repository:** <https://github.com/jasonmeverett/cloudera-ai-agent-studio-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "jasonmeverett-cloudera-ai-agent-studio"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jasonmeverett-cloudera-ai-agent-studio` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jasonmeverett-cloudera-ai-agent-studio/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt