"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.

An MCP server providing AI-powered cybersecurity, penetration testing, reconnaissance, vulnerability assessment, and security automation tools through the Model Context Protocol.

Enables structured multi-perspective debates with Wind (explore), Wall (constrain), and Door (synthesize) roles, featuring deterministic state, hash chains, GitHub integration, and auto-orchestration for decision-making.

Linux desktop HAL for AI agents. One daemon, one socket, every desktop action. GNOME, KDE, Hyprland, X11. Ships in one command.

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 autonomous agents and MCP clients to decompose text into atomic claims and verify them against reference knowledge, detecting ungrounded claims, numerical contradictions, and hallucinated entities.

Enables AI agents and MCP clients to decompose text into atomic claims and cross-verify them against reference knowledge to flag ungrounded claims, numerical contradictions, and hallucinated entities. Runs deterministically with zero dependencies over JSON-RPC stdio, avoiding LLM round-trips for routine verification tasks.

Human-in-the-loop MCP hub for Claude Code agents, enabling agents to ask questions, request approval, or report status to a human via an Obsidian plugin.

A self-hosted MCP server for Home Assistant that exposes full control over entity states, service calls, history, templates, and areas via local stdio, enabling AI assistants to manage your smart home.

An MCP server that lets AI agents autonomously buy physical hats using USDC on Base — no credit card, no checkout, no human required. Browse the catalog, get a real-time shipping quote, send crypto, and we ship the hat.

Enables goal-driven mission orchestration for Goose, turning a user goal into a structured plan with an approval gate, isolated workers in git worktrees, dual validation, auto-correction, and crash recovery to produce validated code.

Provides a human-agent interface control plane for managing agent state, focus, and next steps across any MCP-compatible client, without calling an LLM itself.

Reflexive Memory for AI Agents - MCP Server. Remembers, forgets, questions, and bites.

A local-first MCP memory server that gives AI coding agents persistent memory with hybrid semantic and keyword retrieval, working fully offline.

MCP server wrapping Claude CLI, enabling any MCP host like Cursor to use Claude as a sub-agent with dispatch modes.

Generates a pytest suite from acceptance criteria withheld from the coding agent, so the tests can disagree with the code; qikly_run never returns the criteria. The CLI also scores an existing suite by planting faults, and ships as an agent Skill (qikly --install-skill). Runs locally (uvx --from "qikly[mcp]" qikly-mcp): your code and API key stay on your machine.

A model-neutral cyber capability brain for AI agents and human researchers, providing MCP tools for knowledge ingestion, composition, campaign planning, fleet management, evidence binding, and discovery replay.

Enables autonomous AI agents to safely inspect, configure, and visually validate remote Home Assistant dashboards, automations, and scripts.

Enables agent frameworks to persist deterministic state through ACID PostgreSQL WAL checkpoints, recover the latest checkpoint after restarts or eviction, and roll back session mutations via Saga compensation.

A Model Context Protocol server that connects multiple AI models into a single workflow, enabling multi-model orchestration, conversation continuity, and tools like code review, planning, and CLI-to-CLI bridging.

A Model Context Protocol server that gives Claude access to Google's Gemini 2.5 Pro for extended thinking, code analysis, and problem-solving with a massive context window.

Enables AI assistants to orchestrate multiple models from different providers within a single conversation, supporting collaborative code review, planning, debugging, and implementation workflows with full context continuity.