"HAL" matching MCP servers:

Provides access to 70 paid APIs as MCP tools with per-call and session budgets, paying via x402/USDC on Base without requiring an account or login. Includes a built-in allowlist of hosts and safe defaults to prevent unintended payments.

MCP server for Hyperliquid that provides read-only on-chain wallet analytics. Enables natural-language queries about positions, fills, funding, and realized PnL for any public address.

Enables agents to deploy software via GitHub Actions only with a signed receipt, providing gated tools to resolve refs, list deployments/environments, and dispatch pipelines for a specific commit.

A comprehensive MCP server that enables AI assistants to interact with Home Assistant, control smart home devices, query states, execute services, and manage automations via natural language.

A lightweight, self-hosted MCP server that connects LLM-based agents to Red Hat Lightspeed services, enabling natural language querying of read-only (and optionally write) operations across Advisor, Image Builder, Inventory, Planning, Remediations, and Vulnerability services.

Connects AI assistants to Cal.com for managing bookings, event types, and availability through natural language.

Phone, SMS & email for AI agents. One remote MCP server (Streamable HTTP, OAuth or API-key auth, no local install) exposing call, sms, email, and event tools; also usable via CLI, Python SDK, and OpenAPI. Self-hostable, AGPLv3.

Provides secure, read-only semantic access to Home Assistant entities, areas, floors, and domain summaries for MCP clients like ChatGPT and Codex.

Provides persistent, scoped shared memory for collaborating AI agents, with tools for storing observations, semantic recall, and handoff workflows. Backed by PostgreSQL and exposed through MCP.

Detect fabrication and hallucination in any LLM output. Score responses from GPT-4o, Claude, Gemini, Llama and 30+ models. Free tier included.

Enables estimating LLM hallucination and confabulation by clustering sampled responses into semantic equivalence classes and computing semantic entropy. It provides a plug-and-play validation filter for agent pipelines using the MCP protocol.

Enables detecting LLM hallucinations and confabulations by clustering sampled responses into semantic equivalence classes and computing semantic entropy.

Enables deterministic auditing of RAG retrieval faithfulness and hallucination scores, providing structured JSON output for AI agents and MCP-compliant clients.