Backplane
Backplane Docs https://backplane.gsmlg.net

Backplane Docs

Public gateway references for MCP tools, model traffic, skills, agent setup, and authentication.

Agent setup

Agent setup

Use the configured Backplane origin for ChatGPT, Claude Code, and Codex without embedding real credentials.

Keep endpoints distinct

MCP clients connect to https://backplane.gsmlg.net/mcp; model clients use https://backplane.gsmlg.net/v1. Resource-bound OAuth access tokens are audience-specific, so use separate $MCP_ACCESS_TOKEN and $LLM_ACCESS_TOKEN values. PAT and legacy credentials follow the configured compatibility policy.

Setup

  1. For ChatGPT, register the exact callback it supplies, select the predefined OAuth client, and configure the MCP endpoint.
  2. For Claude Code, configure the Anthropic-compatible /v1 base URL and add Backplane as an HTTP MCP server.
  3. For Codex, define a Backplane model provider and MCP server, with token values supplied through environment variables.

Examples

ChatGPT MCP configuration

MCP server URL: https://backplane.gsmlg.net/mcp
OAuth client ID: $CLIENT_ID
OAuth client secret: $CLIENT_SECRET

Claude Code configuration

export ANTHROPIC_BASE_URL="https://backplane.gsmlg.net"
export ANTHROPIC_AUTH_TOKEN="$LLM_ACCESS_TOKEN"
claude mcp add --transport http --header "Authorization: Bearer $MCP_ACCESS_TOKEN" backplane "https://backplane.gsmlg.net/mcp"

Codex configuration

# Shell
export BACKPLANE_LLM_ACCESS_TOKEN="$LLM_ACCESS_TOKEN"
export BACKPLANE_MCP_ACCESS_TOKEN="$MCP_ACCESS_TOKEN"

# ~/.codex/config.toml
# Replace this placeholder with a model alias exposed by Backplane.
model = "your-backplane-model-alias"
model_provider = "backplane"

[model_providers.backplane]
name = "Backplane"
base_url = "https://backplane.gsmlg.net/v1"
env_key = "BACKPLANE_LLM_ACCESS_TOKEN"

[mcp_servers.backplane]
url = "https://backplane.gsmlg.net/mcp"
bearer_token_env_var = "BACKPLANE_MCP_ACCESS_TOKEN"

Reference

ChatGPT Claude Code Codex MCP /mcp LLM API /v1