Inferenceindexer MCP vs Model Price Radar
A side-by-side look at the Inferenceindexer MCP and Model Price Radar MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Inferenceindexer MCP for conversational ai work as a local process; choose Model Price Radar 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 Inferenceindexer MCP when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
II_API_BASE, II_API_KEY, II_SSR_SECRET. - You want tools like
search_models, get_model, get_model_history.
Choose Model Price Radar when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
find_models, estimate_cost, model_price_history.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Conversational AI | Conversational AI |
| Quality signal | 49/100 · Fair | 53/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | II_API_BASEII_API_KEYII_SSR_SECRET | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 0 |
| Directory activity | 1 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 8 | 5 |
| Full listing | View Inferenceindexer MCP | View Model Price Radar |
Tools & capabilities
Inferenceindexer MCP tools 8
search_modelsSearch/list models with current pricing (by text, tier, sort)get_modelFull detail + current price for one modelget_model_historyHistorical** price trends for one model (the differentiator)list_providersAll providers with model counts + price statsget_providerDetail for one provider (models, tiers, price range)get_composite_latestCurrent SIT-Composite index value + tier breakdownget_composite_historySIT-Composite index history / trendcompare_providersPrice of one model across all providers that host it
Model Price Radar tools 5
find_modelsSearch the live catalog by name, capabilities (tools, vision, reasoning, structured outputs, audio, free), price ceilings, contextestimate_costCost of a workload (tokens per call × calls) on up to 10 models, cheapest firstmodel_price_historyEvery price change of one model since it appeared, with % changesprice_changesSince a month: biggest drops and increases, newly free models, models added/removedcompare_providersSame model across providers: price, context, max output, quantization, uptime
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.
Inferenceindexer MCP
{
"mcpServers": {
"inferenceindexer-mcp": {
"command": "uvx",
"args": [
"inferenceindexer-mcp"
],
"env": {
"II_API_BASE": "YOUR_II_API_BASE_HERE",
"II_API_KEY": "YOUR_II_API_KEY_HERE",
"II_SSR_SECRET": "YOUR_II_SSR_SECRET_HERE"
}
}
}
}
Model Price Radar
{
"mcpServers": {
"model-price-radar": {
"command": "uvx",
"args": [
"model-price-radar-mcp"
]
}
}
}
Frequently asked questions
Inferenceindexer MCP is categorized under Conversational AI and uses a local stdio subprocess. Model Price Radar belongs to Conversational AI and uses a local stdio subprocess. Pick Inferenceindexer MCP for conversational ai work and Model Price Radar 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.
Inferenceindexer MCP has no declared pricing — check the project's own site. Model Price Radar is listed as free. Auth: no auth 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 inferenceindexer-mcp and model-price-radar as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Inferenceindexer MCP has a quality signal of 49/100 (Fair) with 1 views, 0 installs and 0 GitHub stars. Model Price Radar has 53/100 (Good) with 1 views, 0 installs and 0 GitHub stars.