@compute-finance/mcp is a live AI compute pricing oracle that delivers real-time LLM model prices from major providers (Anthropic, OpenAI, Google, xAI) and tools to analyze cost, compare models, and audit Claude Code sessions.

Live Pricing Data

• Full model basket (data_get_basket): all tracked models with provider, family, input/output USD prices per million tokens, and cache pricing components.

• Single model price (data_get_price): lookup by canonical name (e.g., claude-opus-4.7, gpt-5.5) for basket and catalog-only models.

• Full model catalog (data_get_catalog): every tracked model including non-index entries with current prices and cache/reasoning blocks.

• Compute Price Index (data_get_cpi): raw oracle response with all pricing, SCU, and basket version data.

SCU (Standard Compute Unit) & Index

• Current SCU (data_get_scu): per-family blended-cost breakdown and inverse computeIndex purchasing-power view.

• Detailed breakdown (data_get_breakdown): per-family blended costs attributed to model families.

• SCU at timestamp (data_get_scu_at): step-function point lookup without interpolation.

• Baseline SCU (data_get_baseline): frozen genesis denominator for the computeIndex.

Historical Data

• SCU time series (data_get_history): per-revision, daily, or weekly granularity over any date range.

• Model price history (data_get_model_price_history): input/output USD price series for any basket model.

• Model price at date (data_get_model_price_at): effective price at a specific timestamp.

• Basket reconstitutions (data_get_reconstitutions): model swaps with SCU before/after values.

• Methodology changelog (data_get_methodology): every methodology version with formula, family rules, and spec links.

Cost Estimation & Comparison

• Estimate cost (compute_estimate): nominal USD cost for any tracked model given input/output token counts.

• Compare models (compute_compare): ranked list of basket models by cost for a workload, grouped by family.

Claude Code Session Analysis

• Session cost report (render_session_report): formatted report with prompts, tool calls, tokens, and cost for a session.

• Per-inference breakdown (render_consumption_report): bar chart and per-reply cost breakdown with cache hit ratios.

• Active sessions overview (render_active_sessions): table of recent sessions with cost summaries.

• Raw session JSON (analyze_session): token totals, effective/nominal cost, cache breakdown, and counterfactual costs across all basket models.

• Raw inference JSON (analyze_inferences): per-inference data including tool usage, cache hit ratio, and duration.

Aggregate Telemetry

• Session history stats (telemetry_get_history): cumulative cost, per-profile medians, and cache insights across all logged sessions.

Cost Hook Integration

• Automatically injects session cost summaries into Claude's context for real-time display during conversations (Claude Code specific).

Provides real-time pricing data for Google's LLM models, including per-model input/output costs and cache pricing.

Provides real-time pricing data for OpenAI's LLM models, including per-model input/output costs and cache pricing.

1. Click on "Install Server".

2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.

3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@@compute-finance/mcp compare GPT-4o and Claude 3.5 Sonnet pricing"

That's it! The server will respond to your query, and you can continue using it as needed.

Here is a step-by-step guide with screenshots.