"Maintaining Consistent Behavior in System Prompts" matching MCP servers:

High-frequency (~60Hz) in-browser behavior tree execution engine for autonomous AI agents. Reactive priority interrupts, safety guardrails & deterministic action replay over MCP.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Governance framework for LLM agents. Exposes seven mechanically-enforced rules plus tools for preflight file protection, audit-chain verification, session handoff and worklog templates, MCP config auditing, and an emergency kill switch.

Enables hot-reloadable prompt templates with structured reasoning frameworks, quality gates, and multi-step chain workflows that can be version-controlled and executed immediately without restarts.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Cryptographic identity and trust protocol for AI agents. 38 MCP tools across 8 protocol layers: Ed25519 identity, delegation chains, values compliance, signed communication, policy engine, task coordination, cross-layer integration, and agentic commerce. 264 tests passing.

Pre-trade risk validation and position sizing for AI trading agents via G-formula and Iron Fist.

MCP server that coordinates autonomous infrastructure health monitoring agents, enabling natural-language telemetry queries and automated diagnosis, remediation, and verification.

An agentic file-system assistant that lets users read, write, list, and search local files through natural language, using a LangChain agent with an Ollama LLM backed by a FastMCP server.

A production-grade MCP server with 6 sandboxed tools and an agent orchestration engine for autonomous task completion, featuring an evaluation suite with CI/CD quality gates.

Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.

An AI-guided conversation-driven development framework that helps build MVPs and POCs rapidly through intelligent dialogue with specialized MCP services.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Enables real-time full-duplex voice agents to classify user interruptions, backchannels, and acoustic echo, and to arbitrate turn-taking with context rollback via MCP.

Enables real-time voice agents to arbitrate full-duplex speech by classifying user interruptions, backchannels, and acoustic echo while supporting context rollback.

An AI desire-driven system that maintains nine core drive dimensions, generates thoughts and behavior suggestions, and provides tools to inspect and trigger events via MCP.

MCP server that simulates an AI's desire-driven internal state with nine dimensions, event-based updates, dynamic heartbeat, thought pool, and persistent storage, enabling behavior suggestions and inner monologue generation.

A state-based agent orchestration system that allows transitions between different states (IDLE, PLANNING, RESEARCHING, EXECUTING, REVIEWING, ERROR) while maintaining conversation context and providing state-specific prompts.

Provides AI agents with low-latency reflex tools for fast safety checks, option selection, verification, and scoring using calibrated probabilities, reducing reliance on slow LLM deliberation.

Enables AI agents to create, manage, and search hierarchical plans with phases, tasks, and milestones through a comprehensive planning API. Supports CRUD operations, batch updates, rich context retrieval, and artifact management for structured project planning.