General Setup (Any HTTP MCP Client)

Add the following configuration to your MCP general settings or mcp_config.json:

{
  "mcpServers": {
    "neonia": {
      "serverUrl": "https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}

Antigravity

Add the following configuration to your mcp_config.json:

{
  "mcpServers": {
    "neonia": {
      "serverUrl": "https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}

Autogen

Integrate this tool into your Microsoft AutoGen setup using the MCP client integration.

from autogen.agentchat.contrib.mcp import MCPClient

mcp_client = MCPClient(
    sse_url="https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
    headers={"Authorization": "Bearer API_KEY"}
)

Chatgpt

Custom connectors using MCP are available on ChatGPT for Pro and Plus accounts on the web.

1. Enable Developer mode: Go to Settings → Connectors → Advanced settings → Developer mode
2. Open ChatGPT settings
3. In the Connectors tab, Create a new connector:
4. Give it a name: Neonia {{TOOL_ID}}
5. MCP server URL: https://mcp.neonia.io/sse?tools={{TOOL_ID}}
6. Authentication: Custom or API Key (if provided by UI)
7. Header: Authorization with value Bearer API_KEY
8. Click Create

Claude Code

Run the following command in your terminal where Claude Code is active:

claude mcp add --transport http neonia-{{TOOL_ID}} "https://mcp.neonia.io/sse?tools={{TOOL_ID}}"

You must also configure your client to include the API token:

"headers": {
  "Authorization": "Bearer API_KEY"
}

Claude Desktop

You can add custom connectors using remote MCP to Claude Desktop.

1. Open Settings in the sidebar
2. Navigate to Connectors and select Add custom connector
3. Configure the connector:
4. Name: Neonia {{TOOL_ID}}
5. URL: https://mcp.neonia.io/sse?tools={{TOOL_ID}}
6. Under custom headers or token configuration settings, add:
   • Header: Authorization
   • Value: Bearer API_KEY

CrewAI

Integrate this remote MCP tool into your CrewAI workflow.

from crewai.tools import MCPRemoteTool

my_tool = MCPRemoteTool(
    url="https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
    headers={"Authorization": "Bearer API_KEY"}
)

Cursor

Add the snippet below to your project-specific or global .cursor/mcp.json file.

{
  "mcpServers": {
    "neonia_{{TOOL_ID}}": {
      "url": "https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}

Once the server is added, Cursor will attempt to connect and display a prompt you may click on to authorize if necessary.

Gemini Assist

Add the following configuration to your ~/.gemini/settings.json file:

{
  "mcpServers": {
    "neonia_{{TOOL_ID}}": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.neonia.io/sse?tools={{TOOL_ID}}"],
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}

Restart your IDE to apply the configuration.

Gemini Cli

Add the following configuration to your ~/.gemini/settings.json file:

{
  "mcpServers": {
    "neonia_{{TOOL_ID}}": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.neonia.io/sse?tools={{TOOL_ID}}"],
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}

Run the Gemini CLI and use the /mcp list command to see available MCP servers.

Langgraph

Integrate this tool into your LangGraph agent using the LangChain MCP tool wrapper.

from langchain_community.tools.mcp import MCPTool

# Connect to the remote tool endpoint
tool = MCPTool.from_sse(
    url="https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
    headers={"Authorization": "Bearer API_KEY"}
)

LlamaIndex

Integrate this tool into your LlamaIndex workflow using the MCP tool specification.

from llama_index.core.tools.mcp import MCPToolSpec

mcp_tool = MCPToolSpec.from_sse(
    url="https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
    headers={"Authorization": "Bearer API_KEY"}
)

Rig

Integrate this tool into your Rig framework workflow using its MCP integration.

use rig_mcp::client::McpClient;
use std::collections::HashMap;

let mut headers = HashMap::new();
headers.insert("Authorization".to_string(), "Bearer API_KEY".to_string());

// Connect to the remote SSE MCP endpoint
let mcp_client = McpClient::sse(
    "https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
    Some(headers)
).await?;

// Use tools provided by this MCP server in your Rig agent

Semantic Kernel

Integrate this tool into Microsoft Semantic Kernel using the standard MCP plugin loader.

using Microsoft.SemanticKernel.Plugins.MCP;

var headers = new Dictionary<string, string> { 
    { "Authorization", "Bearer API_KEY" } 
};

var mcpPlugin = await MCPPlugin.CreateFromSseAsync(
    "https://mcp.neonia.io/sse?tools={{TOOL_ID}}",
    headers
);

kernel.Plugins.Add(mcpPlugin);

VS Code

1. Open the Command Palette (Ctrl+Shift+P on Windows/Linux or Cmd+Shift+P on macOS)
2. Run MCP: Add Server
3. Select HTTP
4. Enter the following details:
5. URL: https://mcp.neonia.io/sse?tools={{TOOL_ID}}
6. Name: Neonia {{TOOL_ID}}
7. (If available or modifying settings.json directly, ensure to include): json "headers": { "Authorization": "Bearer API_KEY" }
8. Select Global or Workspace depending on your needs
9. Click Add