{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_7ha4hvc4zynm","handle":"iflow-mcp-rinadelph-agent-mcp","url":"https://wellknown.network/agents/iflow-mcp-rinadelph-agent-mcp","links":{"self":"https://wellknown.network/agents/iflow-mcp-rinadelph-agent-mcp/record.json","html":"https://wellknown.network/agents/iflow-mcp-rinadelph-agent-mcp","markdown":"https://wellknown.network/agents/iflow-mcp-rinadelph-agent-mcp/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-rinadelph-agent-mcp","status":"https://wellknown.network/api/v1/agents/iflow-mcp-rinadelph-agent-mcp/status","claim":"https://wellknown.network/agents/iflow-mcp-rinadelph-agent-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-rinadelph-agent-mcp/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-rinadelph-agent-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-rinadelph-agent-mcp/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-rinadelph-agent-mcp/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-rinadelph-agent-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_rinadelph-agent-mcp","summary":"AgentMCP v2.5 - Enhanced multi-agent system with tmux integration and worktree support","description":"# Agent-MCP\n\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/rinadelph/Agent-MCP)\n\n> 🚀 **Advanced Tool Notice**: This framework is designed for experienced AI developers who need sophisticated multi-agent orchestration capabilities. Agent-MCP requires familiarity with AI coding workflows, MCP protocols, and distributed systems concepts. We're actively working to improve documentation and ease of use. If you're new to AI-assisted development, consider starting with simpler tools and returning when you need advanced multi-agent capabilities.\n>\n> 💬 **Join the Community**: Connect with us on [Discord](https://discord.gg/7Jm7nrhjGn) to get help, share experiences, and collaborate with other developers building multi-agent systems.\n\nMulti-Agent Collaboration Protocol for coordinated AI software development.\n\n<div align=\"center\">\n  <img src=\"assets/images/agent-network-viz.png\" alt=\"Agent Network Visualization\" width=\"600\">\n</div>\n\nThink **Obsidian for your AI agents** - a living knowledge graph where multiple AI agents collaborate through shared context, intelligent task management, and real-time visualization. Watch your codebase evolve as specialized agents work in parallel, never losing context or stepping on each other's work.\n\n## Why Multiple Agents?\n\nBeyond the philosophical issues, traditional AI coding assistants hit practical limitations:\n- **Context windows overflow** on large codebases\n- **Knowledge gets lost** between conversations\n- **Single-threaded execution** creates bottlenecks\n- **No specialization** - one agent tries to do everything\n- **Constant rework** from lost context and confusion\n\n## The Multi-Agent Solution\n\nAgent-MCP transforms AI development from a single assistant to a coordinated team:\n\n<div align=\"center\">\n  <img src=\"assets/images/dashboard-overview.png\" alt=\"Multi-Agent Collaboration Network\" width=\"800\">\n</div>\n\n**Real-time visualization** shows your AI team at work - purple nodes represent context entries, blue…","publisher":null,"homepage":null,"repository":null,"version":"2.5.0","license":"MIT","protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_rinadelph-agent-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","summary":"pypi","version":"pypi","description":"pypi"}},"derived":{"capabilities":[{"slug":"analytics.reporting","name":"Reporting & Dashboards","confidence":0.882,"provenance":"derived"},{"slug":"knowledge.knowledge-graph","name":"Knowledge Graphs","confidence":0.836,"provenance":"derived"}],"categories":["analytics","knowledge"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp_rinadelph-agent-mcp","registry":"pypi","observedAt":"2026-10-28T06:24:20.861Z","publishedAt":"2026-02-07T13:53:45.096354Z","latestVersion":"2.5.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_rinadelph-agent-mcp","url":"https://pypi.org/project/iflow-mcp_rinadelph-agent-mcp/","firstSeenAt":"2026-09-09T20:25:33.895Z","fetchedAt":"2026-10-28T06:23:01.461Z","normalizedAt":"2026-10-28T06:23:01.461Z"}]},"firstSeenAt":"2026-09-09T20:25:33.895Z","updatedAt":"2026-10-28T06:24:20.861Z"}