recommend_models

shallow

io.github.DesMartin01/inferenceindexer-mcp · Verify this server

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). limit: Max recommendations (1-20, default 5). Returns: ranked recommendations with endpoint_config and ranking evidence.

100.0/100

1 trials · measured 27 days ago

recommend_models scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.DesMartin01/inferenceindexer-mcp, measured 11 Sept 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote + stdio
Credential class
open
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-09-11100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: recommend_models
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recommend_models — Vouch