MCP Server - AeoNut

The AeoNut MCP server connects your AI assistant to your workspace. It works with Claude, Microsoft Copilot, Claude Code, Cursor, VS Code, Windsurf, Gemini CLI, Codex and any other MCP client. Once it’s connected, your assistant can look through your AI visibility, competitors, content map and content library, and then answer your questions or build reports from that data. It uses the same API key as the API, with the default scopes.

Everything the MCP server does is free. It only reads your data and never changes anything in your workspace.

Connect your assistant

The hosted server is at https://mcp.deepsmith.ai/mcp/ws-uuid. Every client below connects the same way, with that URL and an Authorization: Bearer YOUR_API_KEY header that carries your API key. You don’t need to install anything else.

If you have more than one workspace, each one gets its own URL, https://mcp.deepsmith.ai/mcp/ws-uuid, which you’ll find on Settings → MCP server in that workspace. Add one connector per workspace and name each one the way Connecting multiple workspaces describes.

The snippets below use aeonut-acme as the connector name, so swap acme for your own workspace slug.

Claude on the web, the desktop app and Cowork all share one connector, so you only add it once and it follows your account.

Settings → Connectors → Add custom connector
Name it aeonut-acme (see naming), paste https://mcp.deepsmith.ai/mcp/ws-uuid, then Continue
Authentication: No sign-in (this server uses an API key, not OAuth)
Add header → name authorization, value Bearer YOUR_API_KEY
Add, then Connect. You should see 23 read-only tools.

This works for Microsoft Copilot Studio agents, including ones published to Microsoft 365 Copilot. The person who makes the agent adds the server, and each user gives their own key when they connect.

In the agent: Tools → Add a tool → New tool → Model Context Protocol
Server name aeonut-acme (see naming), a short description, Server URL https://mcp.deepsmith.ai/mcp/ws-uuid
Authentication API key → Type Header → name Authorization
Create, then create a connection with Bearer YOUR_API_KEY as the key

claude mcp add --transport http aeonut-acme https://mcp.deepsmith.ai/mcp/ws-uuid \
  --header "Authorization: Bearer YOUR_API_KEY"

Go to Settings → MCP → Add new server, or edit ~/.cursor/mcp.json. For a single project, use .cursor/mcp.json instead.

{
  "mcpServers": {
    "aeonut-acme": {
      "url": "https://mcp.deepsmith.ai/mcp/ws-uuid",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Put this in .vscode/mcp.json, or run MCP: Open User Configuration if you want it in every project. VS Code needs the servers key and "type": "http". Don’t use the older .mcp.json file, because it drops headers without telling you.

{
  "servers": {
    "aeonut-acme": {
      "type": "http",
      "url": "https://mcp.deepsmith.ai/mcp/ws-uuid",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Edit ~/.codeium/windsurf/mcp_config.json. Windsurf calls the URL field serverUrl, so use that name.

{
  "mcpServers": {
    "aeonut-acme": {
      "serverUrl": "https://mcp.deepsmith.ai/mcp/ws-uuid",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Edit ~/.gemini/settings.json, or .gemini/settings.json for a single project. Gemini calls the URL field httpUrl, so use that name.

{
  "mcpServers": {
    "aeonut-acme": {
      "httpUrl": "https://mcp.deepsmith.ai/mcp/ws-uuid",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Edit ~/.codex/config.toml. Codex reads the key from the environment variable you name and sends it as a bearer token, which means the key never has to sit in the file.

[mcp_servers.aeonut-acme]
url = "https://mcp.deepsmith.ai/mcp/ws-uuid"
bearer_token_env_var = "AEONUT_API_KEY"

export AEONUT_API_KEY=YOUR_API_KEY

Any client that speaks MCP over HTTP (Streamable HTTP) will work with the URL and the Authorization header. These ones are known to work the same way:

Zed: Settings → MCP servers, remote server with a headers block
Raycast: AI → MCP servers, HTTP headers Authorization: Bearer YOUR_API_KEY
JetBrains AI Assistant (2025.3+): Settings → Tools → AI Assistant → MCP, remote server, expand HTTP headers
Perplexity: Settings → Connectors → Custom connector, API key auth with header Authorization (remote connectors are on paid plans and still rolling out)

If your client only runs local (stdio) servers, you can bridge it to the hosted server with mcp-remote. The key goes in an env var because mcp-remote splits arguments on spaces and would break the header apart.

{
  "mcpServers": {
    "aeonut-acme": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.deepsmith.ai/mcp/ws-uuid", "--header", "Authorization:${AUTH}"],
      "env": { "AUTH": "Bearer YOUR_API_KEY" }
    }
  }
}

If you don’t have a key yet, you can create one under Settings → API keys in AeoNut. It’s only shown once, so copy it and paste it into the snippet above.

Connecting multiple workspaces

You add one connector per workspace, and each connector gets its own API key. The key decides which workspace you’re in. The workspace id at the end of the URL is only there to keep the URLs distinct.

Name the connector

Your assistant sees each tool as mcp__<connector-name>__<tool>, so the connector name is the only way it can tell your workspaces apart. We suggest naming it like this:

aeonut-<workspace-slug>

Rule	Why
Lowercase letters, numbers and hyphens only	Some clients reject or rewrite spaces and special characters in tool names
Always start with `aeonut-`	Groups your AeoNut workspaces together and separates them from other connectors
Slug is the brand or client name	Stays correct when the plan changes
Slug at most 20 characters	Some clients cap the full tool name at 64 characters, and at 20 the longest AeoNut tool name still fits
Never a plan name, environment or person	Those change, and the name becomes misleading

Workspace	Connector name
Acme Corp	`aeonut-acme`
Acme India	`aeonut-acme-in`
Globex (agency client)	`aeonut-globex`

Names like Other, Scale workspace and test are usually how an assistant ends up in the wrong workspace, so it’s worth renaming each one to something like aeonut-acme or aeonut-globex.

Asking about one workspace

It helps to name the workspace when you ask, like “check usage in acme”. If you don’t, an assistant with several connectors might query all of them and label the results by workspace.

Try asking

“How visible is our brand in AI answers this month compared to last month?”
“Which competitors get cited more than us, and for which prompts?”
“Why isn’t our site cited for our top prompts? Look at the answers.”
“Which topics in our content map have gaps we haven’t written about?”

Next steps

Using the MCP server

What to ask, the ready-made analyses, and the workflows that get the most out of your data.

Tool reference

Every tool, its inputs and what it returns.

Troubleshooting

Problem	Fix
My assistant queried the wrong workspace	Its connectors have vague or similar names. Rename each to `aeonut-<workspace-slug>`, then restart the client or reconnect so it picks up the new tool names.
The server won’t connect	Check the header is `Authorization: Bearer YOUR_API_KEY` and the key hasn’t been revoked or expired.
Some tools are missing	The key lacks that scope. Create a key with the scopes you need.
Claude’s connector dialog says “Sign in now · Detected”	Ignore it and pick No sign-in. The server takes an API key, not OAuth.
VS Code ignores the header	You put it in `.mcp.json`. Use `.vscode/mcp.json` or the user configuration.
ChatGPT connectors	Not supported yet, because ChatGPT only accepts OAuth or open servers and never an API key. See Not yet: ChatGPT.

​Connect your assistant

​Connecting multiple workspaces

​Name the connector

​Asking about one workspace

​Try asking

​Next steps

Using the MCP server

Tool reference

​Troubleshooting

Connect your assistant

Connecting multiple workspaces

Name the connector

Asking about one workspace

Try asking

Next steps

Troubleshooting