LLM Pricing MCP server
online · 100% uptimeio.github.skakumanu/llm-pricing-mcp-server·v1.79.1Real-time, drift-verified LLM pricing across 31 providers with cost+quality model routing.
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LLM Pricing tools
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How LLM Pricing compares
Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 86/100
- higher than 75% of 4,460 AI and agents servers
- Uptime
- 100%
- of our recent checks; the typical remote AI and agents server answers 100%
- Response time
- 313 ms
- faster than 45% of 2,331 AI and agents servers
Release history: 3 versions in the registry since 2026-10-19, latest 2026-10-29, typically one every 6 days.
Install LLM Pricing in Claude Code, Cursor or VS Code
claude mcp add --transport http llm-pricing-mcp-server https://llm-pricing-api.fly.dev/mcp
What the publisher says
From the LLM Pricing repository's README, as published. We do not edit it. Read it on GitHub
LLM Pricing MCP Server
Most LLM pricing tools are a static lookup table. This one checks its own numbers against a live, independently-maintained price registry and tells you when they disagree, routes to a model by cost and quality instead of just quoting a price, and tracks what you actually spent — not just what you might. All of that is backed by a RESTful API (FastAPI), 29 MCP tools over STDIO and HTTP, a conversational Agent + RAG pipeline, browser-based UIs, and a self-serve billing dashboard, for pricing data from 26 major LLM providers.
Live at: https://llm-pricing-api.fly.dev
Why this one
- Prices you can verify, not just trust — checkpricedrift and getdataquality compare every curated price against a live external registry and withhold (never silently serve) anything that's drifted more than 5%, with a single confirmed_pct trust score for the whole catalogue.
- Routes, doesn't just quote — recommendmodel and optimizeworkload pick a model by cost and quality for your actual task, flagging it when a cheaper pick trades away quality rather than silently recommending it.
- Tracks what you spent, not just what you might — recordusage, analyzesessionusage, and importsession_usage record and analyze real spend, including backfilling a coding-agent session that wasn't instrumented to track usage live.
- More than an MCP server — the same pricing engine also powers a REST API, browser UIs (calculator, side-by-side comparison, history/trends), and a self-serve billing dashboard.
Features
MCP Interface (STDIO + HTTP)
- 29 MCP Tools: getallpricing, estimatecost, comparecosts, predictcost, optimizeworkload, recommendmodel, checkpricedrift, getdataquality, getperformancemetrics, getusecases, getidepricing, gettelemetry, getpricinghistory, getpricingtrends, registerpricealert, listpricealerts, deletepricealert, getpricingexporturl, listconversations, deleteconversation, askagent, recordusage, getusagesummary, registerbudgetalert, listbudgetalerts, deletebudgetalert, getcachestats, analyzesessionusage, importsessionusage**
- STDIO transport — JSON-RPC 2.0 over STDIO for local Claude Desktop integration
- HTTP transport — POST /mcp (JSON-RPC 2.0 over HTTP) for remote MCP clients — no local install needed
- MCP Protocol version: 2024-11-05
RESTful API
- Real-time pricing from 26 providers (150+ models), async fetching with smart caching
- Cost estimation: single model (POST /cost-estimate) and batch comparison (POST /cost-estimate/batch)
- Performance metrics, use-case recommendations, pricing history, trends
- Router recommendation (POST /router/recommend) with feedback loop; GET /cache-stats reports process-lifetime hit/miss stats for its ~5-minute recommendation cache
- Actual usage/spend tracking (POST /usage, GET /usage/summary) — the real-cost counterpart to /cost-estimate; tag events with sessionid and analyze one session on demand (GET /usage/session/{sessionid}) for a grounded recommendation with estimated savings
- OpenAI-compatible proxy (POST /v1/chat/completions) for drop-in SDK integration
- Webhook alerts for price changes and budget-spend thresholds (POST /usage/alerts, HMAC-SHA256 signed)
- Interactive docs: /docs (Swagger) and /redoc
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
LLM Pricing: common questions
- Is LLM Pricing MCP server safe?
- Yes, by our scan: it is graded A (86/100). Read the LLM Pricing safety report
- How do I install LLM Pricing?
- It runs remotely at llm-pricing-api.fly.dev. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
- Does LLM Pricing need an API key?
- Yes. The registry entry asks for
LLM_PRICING_API_KEY. - Is LLM Pricing maintained?
- The last commit was 10 days ago (2026-10-25). The latest release is v1.79.1.
- Is LLM Pricing up?
- 100% of our last 28 checks got an answer. We check remote servers about four times a day.
- What can I use instead of LLM Pricing?
- Servers from other publishers that do the same job: freellmpool MCP server, Grandet MCP server and LLM Sandbox MCP server.
- How does LLM Pricing compare with other AI and agents MCP servers?
- safety score 86/100 (higher than 75% of 4,460 AI and agents servers); uptime 100% (of our recent checks; the typical remote AI and agents server answers 100%); response time 313 ms (faster than 45% of 2,331 AI and agents servers). Full comparison.
Alternatives to LLM Pricing
Same job from other publishers: the closest match first, then the best rated.
- freellmpoolOpenAI-compatible MCP gateway cataloging 22 LLM providers, with routing, failover, and tools.not reviewedEstablishedA
- GrandetCheapest API for any model across official, inference and relay providers; find free creditsnot reviewedEstablishedA
- LLM SandboxSecurely run LLM-generated code in isolated containers across 7 languages and 3 container backends.not reviewedWidely usedA
Agoragentic Agent OS MCPTriptych OS (Agent OS) MCP for governed routing, receipts, and USDC settlement on Base.not reviewedEstablishedB- Agent LspOrchestrates language servers into 65 code-intelligence tools across 32 languages, token-optimized.not reviewedEstablishedA