Summary
This server connects Claude to WhichModel's model recommendation API, which helps autonomous agents pick the right LLM for each task based on live pricing data. You ask it a question about what model to use, and it returns a single confident recommendation optimized for cost. Useful when you're building agents that need to route requests across multiple models and want to minimize API costs without manually tracking pricing changes. The service limits free queries, so you'll likely need an API key for production use. Exposes streamable HTTP transport, meaning it works with Claude Desktop and other MCP clients that support remote connections.
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Tools
Public tool metadata for what this MCP can expose to an agent.
6 tools
recommend_modelGet a cost-optimised model recommendation for a specific task. Describe what you need to do and get back the best model with cost estimate, reasoning, and alternatives.6 params
Get a cost-optimised model recommendation for a specific task. Describe what you need to do and get back the best model with cost estimate, reasoning, and alternatives.
Parameters* required
budget_per_callnumberMaximum spend in USD for this single call
complexitystringTask complexity: low, medium, or highone of
low · medium · highdefault: mediumestimated_input_tokensintegerEstimated input size in tokens
estimated_output_tokensintegerEstimated output size in tokens
requirementsobjectAdditional requirements for the model
task_typestringThe type of task you need a model forone of
chat · code_generation · code_review · summarisation · translation · data_extractioncompare_modelsHead-to-head comparison of 2-5 specific models. Compare pricing, capabilities, quality tiers, and optionally project costs based on expected usage volume.3 params
Head-to-head comparison of 2-5 specific models. Compare pricing, capabilities, quality tiers, and optionally project costs based on expected usage volume.
Parameters* required
modelsarrayModel IDs to compare, e.g. ["anthropic/claude-sonnet-4", "openai/gpt-4.1"]
task_typestringTask type for context-aware comparisonone of
chat · code_generation · code_review · summarisation · translation · data_extractionvolumeobjectExpected usage volume for cost projections
get_pricingRaw pricing data lookup for LLM models. Filter by model, provider, price ceiling, and capabilities. Returns structured pricing data for programmatic consumption.7 params
Raw pricing data lookup for LLM models. Filter by model, provider, price ceiling, and capabilities. Returns structured pricing data for programmatic consumption.
Parameters* required
capabilitiesarrayRequired capabilities to filter by
include_deprecatedbooleanInclude deprecated and sunset models in results (default false)default: false
limitintegerMaximum number of results to return (1-100, default 20)default: 20
max_input_pricenumberMaximum input price per million tokens in USD
min_context_windowintegerMinimum context window size in tokens
model_idstringSpecific model ID, e.g. "anthropic/claude-sonnet-4"
providerstringFilter to models from this provider, e.g. "anthropic"
check_price_changesCheck what model pricing has changed since a given date. Useful for monitoring cost changes and spotting new models or deprecations.3 params
Check what model pricing has changed since a given date. Useful for monitoring cost changes and spotting new models or deprecations.
Parameters* required
model_idstringFilter to a specific model
providerstringFilter to a specific provider
sincestringISO date to check changes from, e.g. "2026-04-01"
estimate_costEstimate the cost of a specific workload for a given model. Returns cost per call, daily and monthly projections, and a comparison to the cheapest alternative with equivalent capabilities.4 params
Estimate the cost of a specific workload for a given model. Returns cost per call, daily and monthly projections, and a comparison to the cheapest alternative with equivalent capabilities.
Parameters* required
calls_per_dayintegerExpected number of calls per day (for daily/monthly projections)
input_tokensintegerNumber of input tokens per call
model_idstringModel ID to estimate cost for, e.g. "anthropic/claude-sonnet-4"
output_tokensintegerNumber of output tokens per call
find_cheapest_capableFind the cheapest models that meet specific capability requirements. Useful when you have hard constraints (e.g. must support tool_calling + vision) and want the most cost-effective option.3 params
Find the cheapest models that meet specific capability requirements. Useful when you have hard constraints (e.g. must support tool_calling + vision) and want the most cost-effective option.
Parameters* required
min_context_windowintegerMinimum context window size in tokens, e.g. 128000
quality_floorstringMinimum quality tier: "low" (budget+), "medium" (standard+), "high" (premium+), "frontier" (frontier only)one of
low · medium · high · frontierrequired_capabilitiesarrayCapabilities the model must support, e.g. ["tool_calling", "json_output", "vision"]
Featured
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
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