Agentcents vs ModelShortlist
A side-by-side look at the Agentcents and ModelShortlist MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Agentcents for conversational ai work as a local process; choose ModelShortlist 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 Agentcents when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
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.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Conversational AI | Conversational AI |
| Quality signal | 37/100 · Fair | 57/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | API key required |
| Pricing | Not declared | BYOK (pay the provider) |
| Required env vars | None listed | ARTIFICIAL_ANALYSIS_API_KEYOPENROUTER_API_KEY |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 1 |
| Directory activity | 0 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | Not listed | 3 |
| Full listing | View Agentcents | View ModelShortlist |
Tools & capabilities
Agentcents tools
No tool names declared yet. Check the project README from the listing page.
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.
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.
Agentcents
{
"mcpServers": {
"agentcents": {
"command": "uvx",
"args": [
"agentcents"
]
}
}
}
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"
}
}
}
}
Frequently asked questions
Agentcents is categorized under Conversational AI and uses a local stdio subprocess. ModelShortlist belongs to Conversational AI and uses a local stdio subprocess. Pick Agentcents for conversational ai work and ModelShortlist 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.
Agentcents has no declared pricing — check the project's own site. ModelShortlist is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. 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 agentcents and modelshortlist as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Agentcents has a quality signal of 37/100 (Fair) with 0 views, 0 installs and 0 GitHub stars. ModelShortlist has 57/100 (Good) with 0 views, 0 installs and 1 GitHub stars.