MCP Server Documentation

Connect your AI coding agent to Social media studio using the Model Context Protocol (MCP). This guide covers setup instructions for every major AI agent.

Claude CodeClaude DesktopCursorOpenAI CodexWindsurfVS Code (GitHub Copilot)Gemini CLI
agent — so-me-studio MCP

Prerequisites

  • A Social media studio account with at least one connected social account. Sign up here.
  • An API key generated from Settings > API Access in your dashboard.
  • MCP Endpoint: https://api.so-me.studio/mcp
  • Authentication: Pass your API key via the X-API-Key header.
  • Transport: Streamable HTTP (POST only, stateless mode).
MCP settings in Social media studio, with the server URL and a configuration snippet

Available Tools

Once connected, your AI agent can call 205 tools across more than 30 categories, here is a sample:

Posts & Scheduling

Create, schedule, retry, resubmit, bulk delete posts and view calendar

Post Comments

Add, update, delete, and list comments on posts for team collaboration

Drafts

Create, update, delete drafts and convert them to scheduled posts

Inbox & Saved Replies

Manage conversations, reply to messages, and create saved reply templates

AI Content & Video

Generate captions, images, UGC videos, hook suggestions, and auto-schedule

AI Video / UGC

Generate videos with AI avatars and sounds, browse avatars and music

Analytics

Workspace summary plus detailed Facebook, Instagram, LinkedIn, YouTube, X analytics

Biolinks

Manage biolink pages, buttons, reorder elements, and track analytics

Media Library

List, search, delete files and manage media folders

Teams

List members, invite new members, remove members, and update roles

Templates

Browse content templates by category and render them with custom values

Help & Support

Create support tickets, list tickets, and send messages

Settings & Usage

Get profile, organization details, billing info, and usage breakdown

Approvals

List pending approvals, approve or reject posts with comments

Setup Guides

1/7

Claude Code

Anthropic's agentic coding tool in your terminal

Config: CLI command or .mcp.json

  1. 1Open your terminal and run the following command:
  2. 2Claude Code will now have access to all Social media studio MCP tools.
  3. 3Verify by running /mcp in your Claude Code session to see "so-me-studio" listed.
bash
claude mcp add --transport http so-me-studio \
  https://api.so-me.studio/mcp \
  --header "X-API-Key: YOUR_API_KEY"

Alternative: .mcp.json

json
{
  "mcpServers": {
    "so-me-studio": {
      "type": "http",
      "url": "https://api.so-me.studio/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}

Place this file in your project root for project-scoped access, or at ~/.claude/.mcp.json for global access.

2/7

Claude Desktop

Anthropic's desktop application for Claude

Config: claude_desktop_config.json

  1. 1Open Claude Desktop and go to Settings > Developer > Edit Config.
  2. 2Add the following to your claude_desktop_config.json:
  3. 3Save the file and restart Claude Desktop.
  4. 4Claude will now have access to Social media studio tools in your conversations.
json
{
  "mcpServers": {
    "so-me-studio": {
      "url": "https://api.so-me.studio/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}

Config file location, macOS: ~/Library/Application Support/Claude/claude_desktop_config.json | Windows: %APPDATA%\Claude\claude_desktop_config.json

3/7

Cursor

AI-first code editor built on VS Code

Config: .cursor/mcp.json

  1. 1Open Cursor and go to Settings > MCP, or create .cursor/mcp.json in your project root.
  2. 2Add the following configuration:
  3. 3Save and Cursor will automatically connect to the MCP server.
  4. 4Verify by checking the MCP panel, "so-me-studio" should show as connected.
json
{
  "mcpServers": {
    "so-me-studio": {
      "url": "https://api.so-me.studio/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}
4/7

OpenAI Codex

OpenAI's coding agent for your terminal and IDE

Config: ~/.codex/config.toml

  1. 1Run the following CLI command to add the server:
  2. 2Codex will store the configuration in ~/.codex/config.toml.
  3. 3Verify by running /mcp in a Codex session to see "so-me-studio" listed.
bash
codex mcp add --transport http so-me-studio \
  https://api.so-me.studio/mcp \
  -H "X-API-Key: YOUR_API_KEY"

Alternative: config.toml

toml
[mcp_servers.so-me-studio]
url = "https://api.so-me.studio/mcp"

[mcp_servers.so-me-studio.env_http_headers]
X-API-Key = "SO_ME_API_KEY"

When using env_http_headers, set the SO_ME_API_KEY environment variable in your shell with your actual API key.

5/7

Windsurf

AI-powered IDE by Codeium with Cascade agent

Config: ~/.codeium/windsurf/mcp_config.json

  1. 1Open Windsurf and navigate to Cascade > MCP settings, or edit the config file directly.
  2. 2Add the following configuration:
  3. 3Save the file and restart Windsurf.
  4. 4Cascade will now have access to Social media studio tools.
json
{
  "mcpServers": {
    "so-me-studio": {
      "serverUrl": "https://api.so-me.studio/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}
6/7

VS Code (GitHub Copilot)

GitHub Copilot agent mode with MCP support

Config: .vscode/mcp.json

  1. 1Create a .vscode/mcp.json file in your project root (or use the Copilot settings UI).
  2. 2Add the following configuration:
  3. 3VS Code will prompt you to start the MCP server when Copilot is in Agent mode.
  4. 4Verify by checking the MCP status in the Copilot chat panel, tools from "so-me-studio" should appear.
json
{
  "servers": {
    "so-me-studio": {
      "type": "http",
      "url": "https://api.so-me.studio/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}
7/7

Gemini CLI

Google's AI agent for your terminal

Config: ~/.gemini/settings.json

  1. 1Run the following CLI command to add the server:
  2. 2Gemini CLI will store the configuration in your settings.json.
  3. 3Verify by running /mcp in a Gemini session to see "so-me-studio" listed.
bash
gemini mcp add --transport http so-me-studio \
  https://api.so-me.studio/mcp \
  -H "X-API-Key: YOUR_API_KEY"

Alternative: settings.json

json
{
  "mcpServers": {
    "so-me-studio": {
      "httpUrl": "https://api.so-me.studio/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}

Place in ~/.gemini/settings.json for global access, or .gemini/settings.json in your project root for project-scoped access.

Supported Platforms

Once connected, your agent can post to all platforms you have linked in your Social media studio dashboard:

Twitter / XInstagramLinkedInLinkedIn PagesFacebookTikTokYouTubeThreadsPinterestBlueskyMastodonDiscordSlackWordPressDev.toDribbble

Troubleshooting

Authentication failed / 401 Unauthorized

Double-check your API key is correct and active. Make sure the header is exactly "X-API-Key" (case-sensitive). Generate a new key from Settings > API Access if needed.

SSE / GET requests return 405

Social media studio's MCP server runs in stateless mode using Streamable HTTP transport. Only POST requests are supported. Make sure your agent is configured with HTTP transport, not SSE.

Rate limit exceeded

MCP tool calls are rate-limited based on your subscription plan. Upgrade your plan or wait before retrying. Check your usage in Settings > MCP.

Credits exhausted

Each MCP tool call consumes credits. Check your remaining credits in Settings > MCP and upgrade your plan if needed.

Connection timeout

If your agent times out during connection, increase the timeout settings in your MCP configuration. A value of 30000ms (30 seconds) is recommended.

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