@bsvkey/inference-mcp
Related Servers
Alternatives to @bsvkey/inference-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityFmaintenanceEnables MCP clients to access all endpoints of an x402 gateway by paying real-time microtransactions (USDC on Base) per API call, with automatic tool discovery and spend guardrails.2360 npmMIT
- AlicenseNot gradedqualityFmaintenanceEnables AI agents to pay per call for AI compute in Kaspa (KAS) over HTTP 402, with no account, API key, or human in the loop, settling each request on-chain.4MIT
- AlicenseAqualityCmaintenanceDescription: Pay-per-request access to Claude and GPT models via Bitcoin Lightning using prepaid spend tokens. No accounts, no API keys — just sats.516 npm2MIT

Agentware MCPofficial
AlicenseAqualityCmaintenanceEnables MCP clients to browse and purchase agent packages and pay per call for model inference on Robinhood Chain using USDG, with no account or API key required.9173 npmMIT
@bridgenode/mcpofficial
AlicenseAqualityCmaintenanceEnables AI agents to make pay-as-you-go AI inference requests through x402 with automatic Solana USDC payments, no API keys or registration, while enforcing configurable spending limits.390 npm1MIT No Attribution- AlicenseNot gradedqualityFmaintenanceEnables AI agents to discover, pay for, and retrieve receipts for external APIs via USDC micropayments through the SynapseNetwork Gateway, supporting stdio and Remote MCP.26 npmMIT
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: listing models, running inference, checking balance, and explaining channel setup. There is no meaningful overlap or ambiguity between them.
list_models and open_channel follow a verb_noun pattern, but infer is a bare verb and channel_balance is a noun phrase without an action verb. The names are readable and predictable in context, but the conventions are mixed.
Four tools is well-scoped for a paid inference gateway: discovery, usage, balance checking, and onboarding. Each tool serves a distinct and necessary step in the core workflow.
The core loop of choosing a model, running inference, checking balance, and funding/opening a channel is covered. Minor gaps like detailed transaction history or channel closure are absent, but agents can accomplish the primary purpose without dead ends.