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Cost-optimized LLM model routing recommendations for autonomous AI agents

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Status
Unhealthy
Last Tested
Transport
Streamable HTTP
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Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 6 tool updates
    • First observedcheck_price_changes
    • First observedcompare_models
    • First observedestimate_cost
    • First observedfind_cheapest_capable
    • First observedget_pricing
    • First observedrecommend_model

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TDQS

A4.3/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: check_price_changes monitors historical pricing, compare_models compares specific models, estimate_cost projects workload costs, find_cheapest_capable filters by capabilities, get_pricing provides raw filtered data, and recommend_model offers task-based recommendations. The descriptions explicitly differentiate use cases and direct users to the appropriate tool.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case (e.g., check_price_changes, compare_models, estimate_cost). The naming is predictable and readable throughout, with no deviations in style or convention.

Tool Count5/5

With 6 tools, the server is well-scoped for LLM model selection and pricing analysis. Each tool serves a unique function in the domain, covering monitoring, comparison, estimation, filtering, data retrieval, and recommendation without being overly sparse or bloated.

Completeness5/5

The toolset provides complete coverage for LLM model selection and cost management: it includes monitoring (check_price_changes), comparison (compare_models), cost estimation (estimate_cost), capability-based filtering (find_cheapest_capable), data lookup (get_pricing), and recommendation (recommend_model). There are no obvious gaps, and the tools work together to support end-to-end workflows.

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