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AgentStatus MCP Index

AgentStatus MCP Index

Remote
github.com/Carmel-Labs-IncOther0Updated 1d ago
Repository

About AgentStatus MCP Index

AgentStatus MCP Index is a public remote MCP server for coding agents that need to discover and use MCP servers. It can search the live public Index, recommend a server for a task, and call that server's tools.

Key features

  1. 01Searches the live public MCP Index
  2. 02Recommends servers for a task
  3. 03Calls recommended server tools

Use cases

  1. 01Find an MCP server for a task
  2. 02Get server recommendations from the Index
  3. 03Use tools from a selected server

MCP support

The public remote MCP endpoint lets clients query the Index, receive server recommendations, and call server tools. The README states that no key is required.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://index.mcp.agentstatus.dev/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

AgentStatus MCP Index

Public remote MCP for the AgentStatus MCP Index.

Endpoint, no key:

https://index.mcp.agentstatus.dev/mcp

A coding agent attaches that URL. It can search the live public Index, recommend a server for a job, and call that server's tools.

Cursor

{
  "mcpServers": {
    "agentstatus-index": {
      "url": "https://index.mcp.agentstatus.dev/mcp"
    }
  }
}

Claude Code

claude mcp add --transport http agentstatus-index https://index.mcp.agentstatus.dev/mcp

Codex

[mcp_servers.agentstatus-index]
url = "https://index.mcp.agentstatus.dev/mcp"

License

MIT

Comments

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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.