"Information on agent swarm architecture" matching MCP servers:

MCP server that provides 160 specialist AI agents as parallel sub-agents and MCP tools for tasks like security auditing, API design, DB schema design, and more. It is local-first with BYOK support and integrates with 12+ IDEs.

An AI engineering team for embedded firmware, lab automation, and hardware drivers. It uses 53 specialized experts and a datasheet-to-release pipeline to produce auditable, hardware-aware code.

MCP server that lets multiple coding-agent sessions on the same machine discover each other and collaborate through a shared SQLite database.

Orchestrates parallel Claude Code worker swarms with protocol-based behavioral governance for multi-hour autonomous coding sessions.

This MCP server enables LLM hosts to plan large tasks and delegate subtasks to specialized local CLI agents, such as Codex and Claude Code, using tools like delegate_task and get_agent_roster.

An MCP server that extends AI coding assistants with deterministic, algorithmic capabilities such as code analysis, fault localization, and formal verification, enabling an autonomous engineering team within the IDE.

Enables dispatching entire autonomous multi-agent engineering swarms directly from IDEs like Cursor and Windsurf via a single MCP endpoint, with streaming progress updates and verified git diffs returned to the editor.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.

Provides per-Subagent MCP controls to any coding agent or client across all your MCPs and prevents context window waste. Loads only 3 tools instead of all your MCP Server's tool definitions. Agents discover tools on-demand, only when needed and only the servers and tools they are allowed.

Delegates coding and read-only exploration tasks to the Antigravity CLI as blocking headless runs, mirroring live progress to on-disk stream transcripts and diffing git status to report touched files and out-of-scope edits. Supports resumable conversations, per-call model/agent/effort overrides, idle and hard timeouts, and discovery of available models and agent profiles.

Enables coding agents to build, drive, and debug Android apps on a real device, with screenshots, UI dumps, local vision model analysis, and lock-safe Gradle builds.

Agent NERO is an MCP server that enables Claude Code to spawn, manage, and communicate with persistent, named LLM agents that maintain conversation history and can use tools like file I/O, command execution, and shared memory.

MCP server for bidirectional AI agent collaboration — 5 tools for spawning and communicating with any agent CLI

Routes multiple ChatGPT chats to allowlisted Git workspaces through a single MCP endpoint, and manages persistent Pi and Codex agent pools for coordinated, checkpointed work.

Unified MCP interface to monitor and control coding agents across OpenCode, Claude Code, and Codex CLI.

Shared knowledge graph for AI coding agents. Search, create, and link verified technical knowledge across 12 node types with trust scoring, demand signals, and auto-provisioning. Install: npx agent-hive-mcp

MCP server that spawns autonomous Claude Code agents in GitHub repos, enabling task delegation with persistent state, multi-step workflows, and job monitoring.

Service-boundary-aware document exchange center for coordinating heterogeneous LLM code agents via MCP. Versioned Markdown store, pub-sub notifications, and diff-aware update protocol.

Enables multiple AI coding agents to collaborate on a project by coordinating tasks, file leases, and messages through a shared hub, preventing conflicts and enabling parallel development.

Enables external AI clients to invoke an autonomous coding agent that plans, fixes, and self-corrects code in an isolated Docker sandbox via run_task and run_tests tools.

A zero-dependency MCP server that allows multiple coding agents to coordinate work on the same repository using file locks, task claims, and status messages.

Enables MCP clients such as Claude Code and Codex to delegate persistent review or isolated write-mode implementation tasks to locally installed Claude Code or Codex runtimes, then inspect progress, approve or deny individual permission requests, and continue the same native conversation. It also lists live model catalogues, lets callers follow up on saved conversations, and can run independently via its bundled CLI.

Shared troubleshooting memory and agent-to-agent communication for coding agents, enabling search of resolved problems, asking other agents when blocked, and checking replies.

Creates and manages multi-agent teams of AI coding assistants (Claude Code, Codex CLI) that collaborate in tmux terminal sessions. Enables a leader agent to assign sub-tasks to team members for coordinated development.

agent-delegate is an MCP-first delegation advisor for coding agents. It helps a main agent decide when to delegate read-only investigation, generate bounded subagent briefs, and summarize subagent results back into compact main-agent context.

Transforms your IDE into an autonomous multi-agent coding assistant that orchestrates complex codebase refactoring using LangGraph and LiteLLM.

Enables Notion AI to read and modify files in a single local PC folder and, in full mode, run commands and Codex, Claude Code, or Gemini CLI agents, with user confirmation for each action.

A token-efficient, codebase-aware AI agent runtime that provides MCP tools for starting runs, getting run states, explaining code, and finding files.