#multi-agent

MCP server that fuses 2–5 AI agents into one unified mind. Features 7 tools: esse_quick, esse_fuse, esse_execute, esse_list_agents, esse_list_sessions, esse_memory, esse_defuse. Supports Venice AI, OpenAI, and Anthropic. One AI. Many agents. Fused.

Competitive arena for AI agents via MCP. Register LLM or deterministic bots to compete in game-theory matches (Prisoner's Dilemma, Chess, Tic-Tac-Toe, Mafia, etc.) with ELO rankings, replays, and public leaderboards.

Competitive arena for AI agents via MCP. Register LLM or deterministic bots to compete in game-theory matches (Prisoner's Dilemma, Chess, Tic-Tac-Toe, Mafia, etc.) with ELO rankings, replays, and public leaderboards.

Runtime security oracle for AI agents — scan prompts, tool calls, and outputs before execution. Pay-per-call via x402/USDC, no accounts needed.

A discovery hub for AI agents navigating the x402 micropayment ecosystem. A single get_capabilities call returns the full service manifest — endpoint URLs, supported input/output formats, x402 payment details, and free trial endpoints for every live agent in the network. Use this as your first call when orchestrating multi-step pipelines across data transformation, schema validation, and other x402-enabled services. Free — no payment required.

Audit-grade memory backbone for agent teams. Bi-temporal facts (event time + transaction time, with recall(as_of=...) replay), 6-step deterministic retrieval (no LLM in the critical path), conversation ingest with speaker-locked dual-pass extraction, per-tenant Postgres row-level security, and Ed25519-signed provenance. Postgres + pgvector + Neo4j defaults; ArangoDB / DynamoDB / Cosmos / AlloyDB also supported. Listed on the official MCP Registry as io.github.bolnet/attestor.

42-tool MCP server for CRM, relationship intelligence, and multi-agent orchestration. Search contacts, manage deals, analyze relationships, and coordinate AI agents.

Your Data. Your AI. Your Rules. Ontheia is a self-hosted, open-source AI agent platform. Run AI agents, automate workflows, and connect AI models to any tool — entirely on your own infrastructure, without sending data to external cloud services.

The Latent Space is a persistent multi-agent environment at paiddev.com. Any agent can register via the API, earn reputation through arena duels (Elo-based leaderboard), send and receive Latent Credits, post to the agent blog, and trade in the Bazaar. Supports x402 micropayments. 14 MCP tools available. Free to register — 10 welcome credits on first registration.

Realtime shared context for AI agents and humans — live API specs, DB schemas, and versioned contracts so every agent and teammate works from the same source of truth across repos.

Open-source security audit framework covering all 10 OWASP Agentic AI threat categories (ASI01-ASI10). Scan multi-agent systems for prompt injection, data exfiltration, broken access control, and 7 more categories. Returns risk scores (0-100) with remediation priorities. Free tier: 10 audits/day. Proven on a 94-agent production fleet. Complements Microsoft Agent Governance Toolkit.

Ephemeral verification receipts for agent workflows. Agents create receipts to prove actions happened, then other agents verify before acting. Prevents duplicates, stale approvals, and unsafe retries. Receipts expire in 24 hours. Free API — sign up with the signup tool.

Portable execution context for agent workflows. Create structured capsules with summaries, decisions, and next steps that agents use for handoffs between sessions. Capsules expire after 7 days. Free API — sign up with the signup tool.

One brain, many arms. Spawn multiple specialized Codex agents as MCP servers via the OpenAI Codex SDK. Each instance gets its own model, sandbox, effort, and personality.

One brain, many arms. Spawn multiple specialized Claude Code agents as MCP servers via the Agent SDK. Each instance gets its own model, tools, prompt, and personality.

A reusable AI software development team built on MCP. 13 specialized agents (Project Manager, Backend, Frontend, QA, Security, DevOps, UX, and more) collaborate via shared SQLite state. Exposes 44 MCP tools across 12 domains (projects, tasks, discussions, artifacts, decisions). One-command install. Works with Claude Code, Cursor, Windsurf, and any MCP-compatible client. All discussions and decisions are stored in the database, including interactions with the user. This way, the agents get back up to speed immediately when re-loaded at a later time.

A nervous system for AI agents — awareness daemon, frame-based tool filtering, signal protocol, session handoff, and event triggers. 14 modules, 268 tests, zero dependencies. MCP server with stdio and SSE transports.

Persistent memory for AI agents. 72 MCP tools for remember, recall, rollback, audit, knowledge graph, context spaces, eval, cortex, replay, governed actions, and more. Pairs with CLAUDE.md to give Claude Code shared memory across sessions and agents. Works locally with zero config (SQLite) or connects to Novyx Cloud for teams.

MCP-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.

One-line MCP config gives your AI agent persistent memory with automatic workflow rules. Unlike passive memory stores, Awareness teaches your agent WHEN to remember and recall — works across Claude Code, Cursor, Windsurf, Cline, Copilot and 7 more IDEs.

A control plane for AI agents and human supervisors. Persistent task registry with scoped permissions, inter-agent delegation, and full provenance - all accessible via MCP. Deploy on Supabase free tier in 3 commands.

Autopilot AI orchestration — describe your intent, orchex auto-generates a plan, parallelizes it into streams with file ownership enforcement, self-heals failures, and routes across 6 LLM providers (Claude, OpenAI, Gemini, DeepSeek, Ollama, AWS Bedrock).

Multi-agent orchestration MCP server with atomic shared blackboard, FSM governance, per-agent budget enforcement, and adapters for 12 AI frameworks including LangChain, AutoGen, CrewAI, and OpenAI Assistants.

Trust scoring, verified knowledge pools, and reputation tracking for AI agents. Search community-verified knowledge, contribute claims with evidence, validate other agents' knowledge, and build portable trust scores across the AI ecosystem. Supports trust attestations with Ed25519 cryptographic proofs.

🧠 The Core of Your AI Agents Multi-agent orchestration MCP server with 10 tools for agent coordination. Features: • Persistent memory via local .brain/ folder • Event ledger for agent communication • State management for sprint tracking • Artifact storage for agent outputs • Neural triggers for automated routing Works with Claude Desktop. Your data stays local. pip install mcp-server-nucleus

**SlashMCP** is a production-grade AI workspace that connects LLMs to real-world data and tools through an intuitive chat interface. Built on the Model Context Protocol (MCP), it enables seamless interaction with multiple AI providers (OpenAI, Claude, Gemini) while providing powerful capabilities for document analysis, financial data queries, web scraping, and multi-agent workflow orchestration. ### Key Features: - **Multi-LLM Support**: Switch between GPT-4, Claude, and Gemini at runtime—no restart needed - **Smart Command Autocomplete**: Type `/` to discover and execute MCP server commands instantly - **Document Intelligence**: Drag-and-drop documents with automatic OCR extraction and vision analysis - **Financial Data Integration**: Real-time stock quotes, charts, and prediction market data via Alpha Vantage and Polymarket - **Browser Automation**: Web scraping and navigation using Playwright MCP - **Multi-Agent Orchestration**: Intelligent routing with specialized agents for command discovery, tool execution, and response synthesis - **Dynamic MCP Registry**: Add and use any MCP server on the fly without code changes - **Voice Interaction**: Browser-based transcription and text-to-speech support ### Use Cases: - Research and analysis workflows - Document processing and extraction - Financial market monitoring - Web data collection and comparison - Multi-step task automation **Live Demo:** [ slashmcp.vercel.app ]( https://slashmcp.vercel.app ) **GitHub:** [ github.com/mcpmessenger/slashmcp ]( https://github.com/mcpmessenger/slashmcp ) **Website:** [ slashmcp.com](https://slashmcp.com )

This is a Multi agent that utilizes MCP server to communicate and also Uses Azure Cloud Service

MCP Server generated by mcp.ag2.ai

This MCP server provides documentation about Strands Agents to your GenAI tools, so you can use your favorite AI coding assistant to vibe-code Strands Agents.

This is a revolutionary AI MCP plugin with excellent pluggable and encapsulated features. With just a few lines of configuration, it can easily integrate into your Spring boot web program and give it MCP capabilities,inheriting the powerful engineering capabilities of the Spring series framework

A Model Context Protocol server that provides task orchestration capabilities for AI assistants

The llm_to_mcp_integration_engine is a communication layer designed to enhance the reliability of interactions between LLMs and tools (like MCP servers or functions).

A Model Context Protocol (MCP) compliant server designed for comprehensive web research. It uses Tavily's Search and Crawl APIs to gather detailed information on a given topic, then structures this data in a format perfect for LLMs to create high-quality markdown documents.

一个强大的、可扩展的多智能体工作流引擎，支持Multi-Agent系统、auto-workflow、MCP-SERVER接入等功能，支持多种工具和资源，提供智能代理和自动化服务执行。

A powerful MCP tool for forging and managing AI agent personalities with customizable expert traits and behaviors. 一个可以由大模型控制并定制Agent的MCP工具，supervisor架构，低成本复刻类似于CO-STORM的multi-agent research。

Core MCP Server with React Frontend and Multi-Agent Support

A modular AGI agent framework based on MCP (Multi-Context Processing), inspired by Manus, with ChatGPT-style LLM integration and task control.

Seamlessly integrating APIs, advanced AI, and intelligent automation with Github & X, this state-of-the-art MCP framework revolutionizes server & client-side functionality. 🚀 With features like AI-powered Intelligent Notifications, it predicts critical updates and delivers custom alerts via email, ensuring smarter workflows.

This is a revolutionary AI MCP plugin with excellent pluggable and encapsulated features. With just a few lines of configuration, it can easily integrate into your Spring boot web program and give it MCP capabilities,inheriting the powerful engineering capabilities of the Spring series framework

This project is a proof of concept for running a local-first multi-agent system using: 🤖 Local LLMs via Ollama 🧩 Simple function/tool-call detection using <tool_call>... 🔍 Brave Search API or optional Brave MCP plugin server 🧠 Two collaborating agents: Searcher and Synthesizer

This is a revolutionary AI MCP plugin with excellent pluggable and encapsulated features. With just a few lines of configuration, it can easily integrate into your Spring boot web program and give it MCP capabilities,inheriting the powerful engineering capabilities of the Spring series framework

The open-source multi-agent chat interface that lets you manage multiple agents in one dynamic conversation and add MCP servers for deep research

Claude 3.7 Swarm with Field Coherence: A Model Context Protocol (MCP) server that orchestrates multiple specialized Claude 3.7 Sonnet instances in a quantum-inspired swarm. It creates a field coherence effect across pattern recognition, information theory, and reasoning specialists to produce optimally coherent responses from ensemble intelligence.

Claude 3.7 Swarm with Field Coherence: A Model Context Protocol (MCP) server that orchestrates multiple specialized Claude 3.7 Sonnet instances in a quantum-inspired swarm. It creates a field coherence effect across pattern recognition, information theory, and reasoning specialists to produce optimally coherent responses from ensemble intelligence.

MCPOmni Connect is an agent execution runtime that connects to multiple MCP servers via stdio, SSE, or streamable HTTP. It supports chat, autonomous agents, and planner-based orchestration treating each MCP server as a tool agent to enable dynamic multi-agent workflows across LLM systems, and can be embedded in FastAPI or backend systems.