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LLM Pricing

Real-time, drift-verified LLM pricing across 26 providers with cost+quality model routing.

Connector by skakumanu · GitHub account verified by the MCP Registry

IndexedMITLocal (stdio)Remote (HTTP)
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Install

Works with Claude Code, VS Code, Codex, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/skakumanu-llm-pricing-mcp-server

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Remote endpoint

  • https://llm-pricing-api.fly.dev/mcp Remote (HTTP)

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About

Real-time, drift-verified LLM pricing across 26 providers with cost+quality model routing.

Reviews

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Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools
20 read · 4 write · 3 delete · 2 not yet classified
Secrets
None asked for
Install scripts
Nothing to install (hosted)
Runs as
Hosted (remote endpoint)

Tools by what they do 29

From the running server's own tool list (tools/list) on Oct 25, 2026.

Read 20 · Look things up without changing anything.

  • analyze_session_usage
  • ask_agent
  • check_price_drift
  • compare_costs
  • estimate_cost
  • get_all_pricing
  • get_cache_stats
  • get_data_quality
  • get_ide_pricing
  • get_performance_metrics
  • get_pricing_export_url
  • get_pricing_history
Show 8 more tools
  • get_pricing_trends
  • get_telemetry
  • get_usage_summary
  • get_use_cases
  • list_budget_alerts
  • list_conversations
  • list_price_alerts
  • recommend_model

Write 4 · Create, change, send or run things.

  • import_session_usage
  • record_usage
  • register_budget_alert
  • register_price_alert

Delete 3 · Delete, drop, revoke or wipe things.

  • delete_budget_alert
  • delete_conversation
  • delete_price_alert

Not yet classified 2 · We could not tell from the name and description.

  • optimize_workload
  • predict_cost

Network hosts it talks to 1

  • llm-pricing-api.fly.dev · found in remote endpoint, install command

Tools (29)

As the server listed them on Oct 25, 2026. Descriptions are the server’s own words; hidden characters are shown as [U+…].

  • analyze_session_usage

    Analyze one specific session's actual recorded LLM usage (tagged via record_usage's session_id) on demand: total input/output tokens, total actual cost, and a per-model breakdown if more than one model was used. Also runs the session's own observed token pattern through the same routing engine behind recommend_model / POST /router/recommend to produce a grounded recommendation — or confirm the current choice is already optimal — with the estimated dollar savings or increase versus this session's actual cost. Returns has_data: false with no recommendation if the session_id has no recorded usage…

  • ask_agent

    Ask the LLM Pricing AI agent a question in natural language. Use for complex queries about pricing, model recommendations, cost optimisation advice, or anything that benefits from multi-step reasoning.

  • check_price_drift

    Audit this server's own pricing data against an external reference registry. Prices here are hand-maintained and go stale silently; a price that disagrees with the registry by more than the threshold is automatically withheld from serving the moment it's detected, not just when this tool runs. This reports what's currently withheld and why. The price value itself is never overwritten by the registry. Use when the user asks whether the pricing data is accurate or up to date, or wants to audit a specific provider's rates.

  • compare_costs

    Compare costs for multiple LLM models

  • delete_budget_alert

    Delete a registered budget-spend alert by its ID.

  • delete_conversation

    Delete a specific chat conversation by its ID. Use when the user asks to delete, clear, or remove a past conversation. Use list_conversations first to find the conversation ID.

  • delete_price_alert

    Delete a registered price-change alert by its ID.

  • estimate_cost

    Estimate the cost of using a specific LLM model

  • get_all_pricing

    Get current pricing for all LLM models from all providers

  • get_cache_stats

    Report process-lifetime hit/miss counts, total lookups, and hit rate for the ~5-minute recommendation cache, separately for the recommend_model tool and POST /router/recommend (never combined). Server-operations introspection for confirming the cache is reducing recomputation in production, not a pricing question. Counts reset on process restart; reading them never changes them.

  • get_data_quality

    Report an aggregate accuracy summary for the pricing catalogue: what percentage of models have a confirmed, fresh price, how many are currently withheld due to price drift, how many are newly discovered and not yet priced, and how many confirmed prices are over 90 days old. A single trust signal, distinct from check_price_drift which lists individual disputes. Use when the user asks how accurate or trustworthy the pricing data is, overall.

  • get_ide_pricing

    Get subscription pricing for AI coding IDE tools: GitHub Copilot, Cursor, Windsurf, Claude.ai, JetBrains AI, Amazon Q Developer, and Tabnine. Returns monthly subscription cost, inline completion support, context window, and per-tool strengths. Use this when the user asks to compare IDE AI tools, subscription-based coding assistants, or wants to know which IDE AI fits their budget.

  • get_performance_metrics

    Get performance metrics (throughput, latency, context window) for models

  • get_pricing_export_url

    Generate a download URL for the pricing history export. Returns a URL the user can open in their browser to download snapshot history as CSV (for spreadsheets) or JSON (for code). Use this when the user asks to export, download, or save pricing data.

  • get_pricing_history

    Query historical pricing snapshots recorded over time. Use this to look up past prices for a model or provider, or to see how prices have changed over a given number of days.

Show 14 more tools
  • get_pricing_trends

    Find models whose prices changed the most over a given period. Returns models sorted by absolute percentage price change with a direction label ('increased', 'decreased', or 'unchanged'). Use this to answer questions like 'which models got cheaper this month?' or 'which providers raised prices recently?'

  • get_telemetry

    Get MCP server telemetry and usage statistics including tool usage, response times, and error rates

  • get_usage_summary

    Get a summary of actual recorded LLM spend: total cost, request count, and breakdowns by model and provider, from usage events previously logged via record_usage. Use when the user asks what they've actually spent, as opposed to a hypothetical cost estimate.

  • get_use_cases

    Get recommended use cases and strengths for LLM models

  • import_session_usage

    Bulk-import a completed session's usage in a single call — the retroactive counterpart to record_usage, for when a session wasn't instrumented live. Use when a calling agent (e.g. VS Code Copilot Chat) already has a session's turn-by-turn history in its own local store and wants this server to report on it exactly as if it had been tracked live. Accepts a list of entries under one shared session_id; each entry resolves its input and output tokens independently, either from exact counts when known or by estimating from raw turn text using this server's existing token counter. Cost is always com…

  • list_budget_alerts

    List all registered budget-spend webhook alerts with their IDs and settings.

  • list_conversations

    List stored chat conversation sessions with their IDs, last-updated timestamp, turn count, and a preview of the most recent user message. Use this when the user asks to see their past conversations or chat history.

  • list_price_alerts

    List all registered price-change webhook alerts with their IDs and settings.

  • optimize_workload

    Optimise a multi-task LLM workload by assigning the cheapest qualifying model to each task instead of running everything through one model. Takes a list of workloads (task type + monthly volume + optional quality floor and capability requirements) and returns a per-task model allocation, the total monthly cost, and the saving versus the best single-model deployment. If a monthly budget is given, leftover headroom is spent on the most cost-efficient quality upgrades. Use when the user asks how to cut LLM spend across several task types, or whether tiered model routing is worth it.

  • predict_cost

    Predict the real cost of an LLM call from your actual prompt text — no need to know token counts in advance. Counts tokens locally, infers the task type (or accepts one explicitly), estimates output length from empirical I/O profiles, and returns all models ranked cheapest-first with effective cost after prompt-cache savings. Also surfaces the best quality-per-dollar pick. Use this before making any LLM API call to avoid surprise bills.

  • recommend_model

    Recommend the optimal LLM model from a free-text description of your use case — no need to already know the routing engine's task_type vocabulary. Classifies the description into a task type, then runs it through the same routing engine behind /router/recommend (live pricing + benchmark quality, hard filters for cost/quality/context window, scored by quality-per-dollar). Returns the best match plus up to 3 alternatives. Read-only — use predict_cost first if you also want per-model cost estimates for an actual prompt, and optimize_workload if you have several distinct task types to route at onc…

  • record_usage

    Record actual token usage for a completed LLM call. Cost is computed server-side from current pricing, never trusted from the caller — this is the 'actual spend' counterpart to estimate_cost's hypothetical numbers. Optionally scope to an org_id for per-org spend tracking. Resubmitting the same request_id for the same org is a no-op. Use when the user wants to log or track real LLM spend, not just estimate it.

  • register_budget_alert

    Register a webhook URL to receive notifications when actual recorded spend (from record_usage) crosses a USD threshold within a rolling window. Optionally scope to a specific org_id (omit for total spend across all orgs). Fires at most once per period_days while spend stays over threshold. Returns the alert ID.

  • register_price_alert

    Register a webhook URL to receive notifications when a model's price changes by more than a specified percentage. Optionally scope the alert to a specific provider or model. Returns the alert ID.

Signals

Stars
0
Forks
1
Open issues
0
Last commit
Oct 24, 2026 (4 days ago)
Last release
Oct 25, 2026 (3 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name
io.github.skakumanu/llm-pricing-mcp-server
Version
1.73.10
Auth
Auth not stated
Packages
npm llm-pricing-mcp
License
MIT
Repository
github.com/skakumanu/llm-pricing-mcp-server
First seen
Oct 24, 2026
Last checked
Oct 26, 2026
Source
Official MCP Registrygithub-graphql
Cite this page

LLM Pricing MCP server. Agent Mart. https://agentmart.dev/connectors/skakumanu-llm-pricing-mcp-server (last updated 2026-10-26)