ModelShortlist vs Tokencost Dev
A side-by-side look at the ModelShortlist and Tokencost Dev MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose ModelShortlist for conversational ai work as a local process; choose Tokencost Dev for conversational ai as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose ModelShortlist when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
ARTIFICIAL_ANALYSIS_API_KEY, OPENROUTER_API_KEY. - You want tools like
recommend_models, compare_models, modelshortlist_status.
Choose Tokencost Dev when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- You want tools like
get_model_details, calculate_estimate, compare_models.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Conversational AI | Conversational AI |
| Quality signal | 57/100 · Good | 60/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | API key required | Not declared |
| Pricing | BYOK (pay the provider) | Not declared |
| Required env vars | ARTIFICIAL_ANALYSIS_API_KEYOPENROUTER_API_KEY | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 1 |
| Directory activity | 0 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 3 | 4 |
| Full listing | View ModelShortlist | View Tokencost Dev |
Tools & capabilities
ModelShortlist tools 3
recommend_modelsThe primary workload-specific recommendation tool. It accepts hard constraints such as:compare_modelsReturns OpenRouter catalog information, ZDR availability, Artificial Analysis benchmark information when available, and source freshness for a specified shortlist of OpenRouter model IDs.modelshortlist_statusShows source freshness, OpenRouter catalog coverage, ZDR coverage, model matching coverage, ambiguous/unmatched records, cache state, and Artificial Analysis rate-limit metadata.
Tokencost Dev tools 4
get_model_detailsLook up pricing, context window, and capabilities for an LLM model. Uses fuzzy matching so you don't need the exact model key.calculate_estimateEstimate the cost for a given number of input and output tokens on a specific model. Supports optional cached_tokens for prompt caching discounts.compare_modelsFilter and compare models by provider, minimum context window, or mode. Returns top 5 most cost-effective matches.refresh_pricesForce a re-fetch of pricing data from the LiteLLM registry. Use this if you suspect the cached data is stale.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
ModelShortlist
{
"mcpServers": {
"modelshortlist": {
"command": "npx",
"args": [
"-y",
"@agentic.artists/modelshortlist"
],
"env": {
"ARTIFICIAL_ANALYSIS_API_KEY": "YOUR_ARTIFICIAL_ANALYSIS_API_KEY_HERE",
"OPENROUTER_API_KEY": "YOUR_OPENROUTER_API_KEY_HERE"
}
}
}
}
Tokencost Dev
{
"mcpServers": {
"tokencost-dev": {
"command": "npx",
"args": [
"-y",
"tokencost-dev"
]
}
}
}
Frequently asked questions
ModelShortlist is categorized under Conversational AI and uses a local stdio subprocess. Tokencost Dev belongs to Conversational AI and uses a local stdio subprocess. Pick ModelShortlist for conversational ai work and Tokencost Dev for conversational ai.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
ModelShortlist is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. Tokencost Dev has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add modelshortlist and tokencost-dev as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, ModelShortlist has a quality signal of 57/100 (Good) with 0 views, 0 installs and 1 GitHub stars. Tokencost Dev has 60/100 (Good) with 1 views, 0 installs and 1 GitHub stars.