# Agent Dash

> Agent Dash — prajeevan-agent-dash. Use this tool when you need to facilitate communication between AI agents and users, enabling agents to send updates and receive answers in real-time. Agent Dash solves problems of asynchronous communication and delayed responses by providing a push inbox for agents to wait for user input before proceeding. It takes in agent updates and questions as input and outputs user answers, ideal for use cases requiring interactive and dynamic agent-user interactions.

Canonical page: https://skillsregistry.net/skills/prajeevan-agent-dash  
JSON: https://api.skillsregistry.net/v1/skills/prajeevan-agent-dash

## Description

A self-hosted push inbox for AI agents that enables agents to send updates and ask questions, waiting for user answers before continuing.

## Trust

- **Trust score (0–1):** 0.54
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/bn1sb91y49)
- **Repository:** <https://github.com/Prajeevan/agent-dash>

## 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": "prajeevan-agent-dash"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/prajeevan-agent-dash` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/prajeevan-agent-dash/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