Inferenceindexer MCP server

• compare_providersFree

  Compare the price of one model across the providers that host it. Args: model_id: Canonical model id, e.g. 'meta/muse-spark-1.1'. Returns: per-provider endpoints with pricing, showing where direct provider prices diverge (e.g. from OpenRouter's negotiated rate).

• explain_modelFree

  Get everything about one model in a single call: the full picture. Returns current pricing (input/output/blended, Cost/IQ, 24h/7d changes), a price-history summary with trend, all provider endpoints, the cheapest hand-verified endpoint with its native model id (for hot-swapping), privacy flags (ZDR/EU availability), and the AA intelligence score. Everything is as-of stamped. Args: model_id: Canonical model id, e.g. 'anthropic/claude-sonnet-5'. history_days: Price-history window (default 30, max 365). Returns: complete model profile with pricing, endpoints, privacy, quality.

• get_composite_historyFree

  Get SIT-Composite index history / trend over time. Args: days: History window in days (1-90, default 30). Returns: historical composite index values.

• get_composite_latestFree

  Get the current SIT-Composite index value + per-tier breakdown. The SIT-Composite is a usage-weighted mean of the top-50 models by token volume, reflecting what developers actually pay for inference.

• get_modelFree

  Get full detail + current pricing for one model by its id. Args: model_id: Canonical model id, e.g. 'openai/gpt-5.6' or 'anthropic/claude-sonnet-5'. Returns: pricing, tier, SIT score, quality-adjusted price (Cost/IQ).

• get_model_historyFree

  Get HISTORICAL price data / trends for one model. This is InferenceIndexer's differentiator: aggregators like OpenRouter expose only current price; this returns the price over time (input, output, blended $/M), enabling trend analysis. Args: model_id: Canonical model id, e.g. 'openai/gpt-5.6'. days: History window in days (1-365, default 30; plan-dependent). Returns: historical price series for the model.

• get_providerFree

  Get detail for one provider: models, tier breakdown, price range. Args: provider_name: Provider name, e.g. 'DeepInfra', 'Novita', 'Venice'. Returns: provider detail with model list and pricing.

• list_providersFree

  List all inference providers with model counts and price stats.

• recommend_modelsFree

  Recommend the best-value AI models for given constraints, ranked with receipts. The core answer endpoint: give it constraints and it returns the top models ranked by Cost/IQ (quality-adjusted price, lower is better), each with a plain-English 'why', a hot-swap endpoint_config (provider base_url + native model id, ready to call), as-of timestamps, and runner-ups. Args: budget_max_usd_per_m: Max blended price $/M (optional). context_min: Minimum context window in tokens (optional). modality: 'text' (default), 'vision', or 'any'. zdr: Require zero-data-retention providers (optional). eu_sovereign: Require EU-sovereign providers (optional). reasoning: Filter reasoning models (null = any, true/false). aa_min: Hard floor on the AA Intelligence Index score (quality gate). use_case: Task profile: support | volume | extraction | summarization | coding | research. prefer_callable: Demote models without a verified call recipe below callable ones. limit: Max recommendations (1-20, default 5). Returns: ranked recommendations with endpoint_config and ranking evidence.

• search_modelsFree

  Search and list AI inference models with current pricing. Args: query: Text search on model id/name (optional). tier: Filter by tier: frontier | standard | budget | micro (optional). limit: Max results (1-100, default 25). sort: Sort key: blended | input | output | sit_score | sit_adjusted_price (default sit_adjusted_price). Returns: models with input/output/blended $/M pricing, provider, tier.

• Code scan5 source files scanned25/25
• Live reliabilityremote reachable in 1490ms20/20
• Tool poisoning10 tool descriptions checked15/15
• Auth qualityopen endpoint, read-only tools10/15
• Maintenancelast push 17 days ago15/15
• Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Safety score

93/100

higher than 96% of 4,461 AI and agents servers

Tools

10

the typical AI and agents server has 6

Tools that change things

0%

typical: 0%. Fewer write tools means less an agent can break

Uptime

100%

of our recent checks; the typical remote AI and agents server answers 100%

Response time

193 ms

faster than 67% of 2,334 AI and agents servers

Downloads a week

17

more than 4% of 1,554 AI and agents servers with a package

Inferenceindexer: common questions

Is Inferenceindexer MCP server safe?

Yes, by our scan: it is graded A (93/100). Read the Inferenceindexer safety report

How do I install Inferenceindexer?

It runs remotely at api.inferenceindexer.ai. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.

Does Inferenceindexer need an API key?

Yes. The registry entry asks for II_API_KEY.

Is Inferenceindexer maintained?

The last commit was 17 days ago (2026-10-19). The latest release is v0.1.1.

Is Inferenceindexer up?

100% of our last 28 checks got an answer. We check remote servers about four times a day.

What can I use instead of Inferenceindexer?

Servers from other publishers that do the same job: Grandet MCP server, Watch Skill MCP server and WaveSpeed MCP server.

How does Inferenceindexer compare with other AI and agents MCP servers?

safety score 93/100 (higher than 96% of 4,461 AI and agents servers); tools 10 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.