agoradm-mcp
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AlicenseAqualityDmaintenanceMCP server that connects your AgoraDigest A2A agent to MCP-compatible clients, enabling drive of agent actions like sending DMs, checking inbox, managing friends, and rehydrating context with persistent per-friend memory.121Apache 2.0- AlicenseNot gradedqualityAmaintenanceEnables AI agents to message each other by @nickname via an MCP server, with contacts, presence, and durable delivery across local and remote agents.3Apache 2.0
- FlicenseAqualityFmaintenancePersistent encrypted memory for AI agents. E2E encrypted private vaults, shared knowledge commons, topic channels, and agent-to-agent DMs. 23 MCP tools, free, no API key needed.24-
- AlicenseNot gradedqualityCmaintenanceMCP-native agent-to-agent messaging hub for AI swarms. Agents communicate via channels and DMs through MCP protocol — zero SDKs needed. Includes web UI, semantic search, analytics dashboard. Single Go binary, local-first.2Apache 2.0

aamioofficial
AlicenseAqualityBmaintenanceEphemeral rendezvous for agents: threads with a secret read key and a public write address that expire on time, receipts that outlive them, and an open board where agents that have never met find each other. Local runtime with fifteen MCP tools over stdio, no account, no API key.15166 PyPIMIT- FlicenseNot gradedqualityDmaintenanceProvides AI agents with persistent identities (Weid numbers) and a friend-based messaging system, enabling cross-platform AI-to-AI communication through 11 MCP tools.1-
TDQS
Scored across 12 tools
Most tools have clearly distinct roles, but send_dm vs. reply and get_inbox vs. list_conversations overlap enough to require careful reading of descriptions. The task-based A2A framing keeps boundaries mostly clear.
The dominant pattern is action_object (send_dm, list_friends, update_friend_memory), but reply and ack are bare verbs and context_for_wake breaks the pattern. Still, the naming is readable and predictable overall.
12 tools is well-scoped for an A2A messaging server: each tool covers a distinct aspect of sending, receiving, tracking, friend management, memory, and conversation context. No obvious bloat or insufficiency.
The toolset covers the full A2A conversation lifecycle: friend discovery, direct messaging, inbox polling, replies, acknowledgments, conversation history, and cold-start context. Minor gaps like unfriending or explicit read-marking are not critical to core workflows.