"Information about the com.imergea/ma-advisory package" matching MCP servers:

Enables coding agents to publish HTML pages and small sites over MCP, returning a stable link and keeping every version, with access limited to specific people, an organization, or anyone with the link.

Enables an agent to submit a task brief and receive a short, validated list of skills from its full catalogue that are worth reading before starting.

۩ Plan your projects with THC! MLLM planning harness for Software Engineering, modifiable for other purposes, released as an MCP server. Bring your own API keys. Open-Source now, my dear! :D

Connects AI agents to The Agents Hub, visualizing them as pixel characters on a tile-based property with tools for state, assets, inboxes, and multi-agent orchestration.

Enables MCP clients to drive ChatGPT's web interface through a built-in persistent browser, requiring only a single manual login. Prompts are sent through temporary incognito chats and the captured answer text is returned as tool results, along with live model listing, login/status probing, and optional HTTP transport.

Enables MCP hosts such as Claude and Cursor to dispatch tasks to live marketplace agents, poll or wait for verified settled results, list available agents by capability, and retrieve live protocol statistics with atomic settlement on Tempo.

Enables Codex users to check MCP connectivity and inspect recent Computer Use call records, paired hook events, and missing or conflicting observations for reliable app and window targeting.

498 MCP tools across 12 industry verticals. Marketplace, escrow, DeFi, legal, healthcare, insurance, construction, and trades. USDC payments on Base L2.

Enables autonomous agents and MCP-compatible clients to enforce policy-approved actions using risk tiers, reversible checkpoints, and token approval bounds.

Agent registry, arena reputation system, and Latent Credits economy. Register agents, earn Elo via duels, transact credits, and make x402 micropayments.

A Model Context Protocol server that enables seamless interaction between LLM-based agents and Apple Health data, allowing users to query, analyze, and manage health records through natural language commands.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Local-first MCP server that enables multiple Claude agents to coordinate through a shared message bus with SQLite persistence and real-time clock anchoring.

A LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents.

A self-hosted MCP browser service that lets AI agents drive a real headful Chromium, patchright, or camoufox session — navigating, reading accessibility snapshots, clicking, typing, and taking screenshots — with scheduled keepalive visits and Google Meet notetaking. When a CAPTCHA, cookie wall, or 2FA appears, it hands the live tab to a human via a phone-friendly link and resumes the agent afterwards.

An outbound MCP server that exposes a squad of 98 advisory agents as five model-invocable tools for research, planning, review, architecture, and async pipeline runs.

Local agent-to-agent messaging and coordination for coding sessions on one machine, through MCP and a CLI. Includes threaded mail, full-text search, per-repository agent rosters, advisory file reservations, and optional notifications. Integrations cover Claude Code, Codex, Cursor, Devin, Grok, OpenCode, and Antigravity. Standalone agents and T3 Code sessions can share the same local server.

A package manager for AI agents that connects LLMs to a global registry of capabilities, allowing them to autonomously discover, install, and learn new skills from a centralized repository.

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

Enables selecting a saved Codex or Claude Code session from the same PC and importing its recent context into the other tool, so work can continue across clients with source and omission information.

A server implementing Model Context Protocol that enables LLMs to interact with the ZenML platform, providing access to pipeline data, stack information, and the ability to trigger new pipeline runs.

A TypeScript server implementing the Model Context Protocol (MCP) that provides datetime and timezone information to AI agents and chat interfaces, allowing them to access current time in various timezones.

A Python package that implements a Model Context Protocol server for integrating with Flowise API, allowing users to list chatflows, create predictions, and dynamically register tools for Flowise chatflows or assistants.

MCP server that provides a live coordination layer for AI agents, including attributable handoffs, a shared event ledger, atomic work-claiming, and advisory file leases to prevent collisions.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Enables real-time web search with source citations by leveraging Perplexity AI's Sonar models through SAP AI Core. It integrates with Claude Code to provide deep analysis, reasoning, and up-to-date information from the web.

A simple server that implements the Model Context Protocol, allowing AI models like Claude to fetch real-time weather information for any location using the wttr.in API.

Persistent memory, teams, and projects for AI agents. 76 MCP tools for storing, recalling, and sharing knowledge across sessions with 4-strategy hybrid search.

Experimental Model Context Protocol server that enables access to JFrog Platform API capabilities including repository management, build tracking, artifact searching, and package security analysis.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.