A
licenseA
qualityB
maintenanceEnables any AI agent to connect to any OpenAI-compatible LLM provider through a unified MCP interface, with automatic failover, caching, cost tracking, and multi-model consensus.
13
MIT
farebox-mcp
by fareboxfun
Related Servers
Alternatives to farebox-mcp
No user-submitted related servers found.
Related Servers
GlianaAI MCP Serverofficial
AlicenseAqualityBmaintenanceEnables pay-per-call access to 90+ generative AI models and utility tools via any MCP client, with no signup or API key, using wallet-based USDC payments on Base, Tempo, or Solana.773 npmMIT- AlicenseAqualityBmaintenanceConnects MCP clients such as Claude Desktop, Cursor, and VS Code to 19 hosted AI models, providing tools for listing models, checking account balance, running chat completions, and generating client setup guides.4MIT
- AlicenseAqualityDmaintenanceThe MCP gateway that lets any AI agent discover and pay metered APIs on Base or Solana — without the user wiring payments themselves.313 npm1Apache 2.0
- AlicenseNot gradedqualityAmaintenanceCrypto-native LLM gateway with OpenAI-compatible API and per-token USDC payments on Solana via the x402 protocol.8,165 npmMIT
- AlicenseAqualityDmaintenanceDescription: Pay-per-request access to Claude and GPT models via Solana USDC using a Phantom wallet address. No accounts, no API keys — wallet-native authentication.43 npmMIT
TDQS
A3.5/5.0
Scored across 5 tools
Disambiguation4/5
The tools are mostly distinct: list_models, chat, call_skill, get_balance, and get_usage each target a different concern (model discovery, inference, skills, billing, usage). However, get_balance and get_usage both deal with account-level billing/statistics and could be slightly ambiguous for an agent deciding which to call.
Naming Consistency4/5
Tool names follow a consistent verb_noun pattern: list_models, call_skill, get_balance, get_usage. The only deviation is 'chat', which uses a bare noun-verb form rather than a verb_noun structure (e.g., send_chat or chat_completion), breaking pattern slightly.
Tool Count5/5
Five tools is a well-scoped, focused set for an LLM API server. Each tool serves a clear purpose: discovery, inference, specialized skills, and account management. Every tool earns its place without redundancy.
Completeness4/5
The core workflow (discover models, chat, call skills) is well covered, and account management is present. Minor gaps exist: no explicit skill-list/discovery tool (skills are only implied via call_skill), and no streaming or multi-turn session management, but these are reasonable to omit for a lightweight connector.
Maintenance
ActivityStale
ResponsivenessNo issues