Model ID Cheatsheet

Stop your AI coding agent from hallucinating outdated model names. This plugin gives any AI assistant instant access to accurate, up-to-date API model IDs, pricing, and specs for 46 models across 7 providers.

Built in Go. Single 10MB binary. Zero external calls. Sub-millisecond responses. Auto-updated weekly.

Why?

When you ask an AI coding agent to "use the latest OpenAI model", it might generate gpt-4-turbo (deprecated) instead of gpt-5.2 (current). This plugin solves that by giving your agent a tool it can call to look up the correct model ID before writing code.

Example: Your agent needs to write an API call. Instead of guessing, it calls get_model_info("gpt-5.2") and gets back the exact API model ID, pricing, context window, and capabilities — verified against official docs.

Install as Plugin (Recommended)

Claude Code Plugin

/plugin marketplace add aezizhu/universal-model-registry
/plugin install model-id-cheatsheet

That's it. Claude Code gets 6 tools + a smart lookup skill that automatically verifies model IDs before writing code.

Alternative: Direct MCP Connection

If you prefer to connect directly to the MCP server without the plugin:

Claude Code (one command)

claude mcp add --transport sse --scope user model-id-cheatsheet \
  https://universal-model-registry-production.up.railway.app/sse

Claude Code can now call list_models, get_model_info, recommend_model, etc.

Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "model-id-cheatsheet": {
      "url": "https://universal-model-registry-production.up.railway.app/sse"
    }
  }
}

Windsurf

Add to your Windsurf MCP config (Settings > MCP Servers):

{
  "mcpServers": {
    "model-id-cheatsheet": {
      "serverUrl": "https://universal-model-registry-production.up.railway.app/sse"
    }
  }
}

Codex CLI

Add to ~/.codex/config.toml:

[mcp_servers.model-id-cheatsheet]
command = "uvx"
args = ["mcp-proxy", "--transport", "sse", "https://universal-model-registry-production.up.railway.app/sse"]

OpenCode

Add to ~/.config/opencode/opencode.json:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "model-id-cheatsheet": {
      "type": "remote",
      "url": "https://universal-model-registry-production.up.railway.app/sse"
    }
  }
}

Any MCP Client (Generic)

Connect to the SSE endpoint:

https://universal-model-registry-production.up.railway.app/sse

No API key needed. No auth. Just point your MCP client at that URL.

Self-Hosting

If you prefer to run your own instance instead of using the hosted one:

Option 1: Docker (Recommended)

git clone https://github.com/aezizhu/universal-model-registry.git
cd universal-model-registry
docker build -t model-id-cheatsheet .
docker run -p 8000:8000 model-id-cheatsheet

Your SSE endpoint will be at http://localhost:8000/sse.

Option 2: Build from Source

Requires Go 1.23+.

git clone https://github.com/aezizhu/universal-model-registry.git
cd universal-model-registry/go-server
go build -o server ./cmd/server

# stdio mode (for local MCP clients like Claude Code local)
./server

# SSE mode (for HTTP-based clients)
MCP_TRANSPORT=sse PORT=8000 ./server

Option 3: Deploy to Railway

Or manually:

railway login
railway init
railway up

Local MCP Config (self-hosted)

For Claude Code connecting to a local instance:

claude mcp add --transport sse --scope user model-id-cheatsheet \
  http://localhost:8000/sse

For Cursor (local):

{
  "mcpServers": {
    "model-id-cheatsheet": {
      "url": "http://localhost:8000/sse"
    }
  }
}

Available Tools

Your AI agent gets these 6 tools:

Resources

Covered Models (46 total)

Current Models (32)

Legacy & Deprecated Models (14)

Also tracked so your agent can detect outdated model IDs and suggest replacements:

• OpenAI: gpt-4.1 (legacy), gpt-4o (deprecated), gpt-4o-mini (deprecated)
• Anthropic: claude-opus-4-5 (legacy), claude-opus-4-1 (legacy), claude-opus-4-0 (legacy), claude-sonnet-4-0 (legacy), claude-3-7-sonnet-20250219 (deprecated)
• Google: gemini-2.0-flash (deprecated)
• xAI: grok-3 (legacy), grok-3-mini (legacy)
• Meta: llama-3.3-70b (legacy)
• Mistral: codestral-2508 (legacy)
• DeepSeek: deepseek-v3 (deprecated)

How It Helps Your Coding Agent

Scenario 1: Writing an API call

You: "Call the OpenAI API with their best coding model"
Agent calls: get_model_info("gpt-5.2-codex")
Agent writes: model="gpt-5.2-codex"  # Correct!

Scenario 2: Checking if a model is still valid

You: "Use gpt-4o for this task"
Agent calls: check_model_status("gpt-4o")
Agent responds: "gpt-4o is deprecated (retiring Feb 13, 2026). I'll use gpt-5 instead."

Scenario 3: Finding the cheapest option

You: "Use the cheapest model that supports vision"
Agent calls: list_models(capability="vision", status="current")
Agent picks: gpt-5-nano at $0.05/$0.40 per 1M tokens

Scenario 4: Comparing options

You: "Should I use Claude or GPT for this?"
Agent calls: compare_models(["claude-opus-4-6", "gpt-5.2"])
Agent gets: Side-by-side table of pricing, context, capabilities

Security

Built-in Protection

• Rate limiting: 60 requests/minute per IP
• Connection limits: Max 5 SSE connections per IP, 100 total
• Request body limit: 64KB max
• Input sanitization: All string inputs truncated to safe lengths
• HTTP hardening: ReadTimeout 15s, ReadHeaderTimeout 5s, IdleTimeout 120s, 64KB max headers
• Non-root Docker: Containers run as unprivileged user
• Graceful shutdown: Clean connection draining on SIGINT/SIGTERM

Staying Up to Date

Model data is automatically checked every Monday via a GitHub Actions workflow. The updater queries each provider's API to detect new models, deprecations, or pricing changes, and opens a GitHub issue if updates are needed. You can also trigger it manually via workflow_dispatch.

Tech Stack

• Language: Go 1.23
• MCP SDK: github.com/modelcontextprotocol/go-sdk v1.3.0 (official)
• Transports: stdio, SSE, Streamable HTTP
• Binary size: ~10MB
• Tests: 96 unit tests
• Security: Per-IP rate limiting, connection limits, input sanitization
• Deploy: Docker (alpine), Railway

Contributing

To add or update a model:

1. Edit go-server/internal/models/data.go
2. Update test counts in go-server/internal/models/data_test.go
3. Run cd go-server && go test ./... -v
4. Submit a PR

License

MIT