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open-multi-agent-kit

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Evidence-gated runner for Codex, Claude Code, OpenCode, and local coding agents. Routes tasks into scoped DAG lanes with replayable artifacts.

MCP Servers84 stars10 forksTypeScriptMITUpdated today
ClaudeWave Trust Score
87/100
Trusted
Passed
  • Open-source license (MIT)
  • Actively maintained (<30d)
  • Clear description
  • Topics declared
Last scanned: 6/11/2026
Install in Claude Code / Claude Desktop
Method: Manual
Claude Code CLI
git clone https://github.com/dmae97/open-multi-agent-kit
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "open-multi-agent-kit": {
      "command": "node",
      "args": ["/path/to/open-multi-agent-kit/dist/index.js"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Clone https://github.com/dmae97/open-multi-agent-kit and follow its README for install instructions.

24 items in this repository

Persistent memory, recall, session replay, and memory-governance workflow adapted from rohitg00/agentmemory for OMK. Use when setting up agent memory, deciding what to remember, importing/replaying sessions, reducing repeated context, or auditing memory safety.

Install

Minimal, goal-driven, surgical coding workflow adapted from forrestchang/andrej-karpathy-skills for OMK. Use for coding, refactoring, debugging, and review tasks where assumptions, overengineering, or broad edits could cause regressions.

Install

Legal workflow drafting, triage, review, research planning, legal operations, law-student or clinic support, and legal AI governance adapted from Anthropic claude-for-legal. Use for commercial, privacy, product, corporate, employment, regulatory, AI governance, IP, litigation, legal-clinic, and law-student tasks. Draft-only; attorney review and current source verification required.

Install

Real-engineering alignment, shared-language, TDD, diagnosis, and architecture-review workflow adapted from mattpocock/skills for OMK. Use before non-trivial implementation, ambiguous product work, debugging loops, test-first changes, or codebase architecture cleanup.

Install
multicaSkill

Managed-agent teamwork, issue assignment, progress tracking, reusable-skill compounding, and handoff workflow adapted from multica-ai/multica for OMK. Use when coordinating multiple agents, converting work into agent-ready tasks, tracking blockers, or turning repeated solutions into skills.

Install

Review AdaptOrch, OMK, and similar DAG multi-agent orchestration frameworks. Use when assessing DAG node responsibility, dependency edges, worker write authority, fallback/retry/timeout/evidence gates, review/merge boundaries, or reproducible decision traces.

Install

Optional read-only OMK web/social/video research workflow inspired by Panniantong/Agent-Reach. Use for web search, current social evidence, YouTube/Bilibili/Reddit/Twitter/X/RSS/GitHub public research, and Agent Reach availability checks without auto-installing or collecting credentials.

Install

Backend API review for NestJS, Express, FastAPI, database access, validation, auth, error handling, and API contracts.

Install

Adversarial code review for diffs, logic correctness, type safety, test coverage, and security risk.

Install

Context and memory policy for long-running Kimi coding sessions, DAG workers, and repeated project work.

Install

Diagnose agent, runtime, tool, hook, context, provider-routing, DAG, retry, fallback, and evidence-gate failures using an industrial automation feedback-control loop. Use when workflows oscillate, stall, lose context, misroute tools, or need setpoint/sensor/controller/actuator/disturbance/correction analysis.

Install

Build and maintain a terminal-native, orchestration-first design system for agent team HUDs, status surfaces, and control planes.

Install

Documentation, changelog, release note, README, migration guide, and developer handoff workflow.

Install

Generate task-specific evidence contracts before a done/completed claim. Use for feature, bugfix, refactor, research, release, security, docs, or orchestration tasks that need changed files, non-empty diffs, test/build/typecheck results, citations, uncertainty, conflicting evidence, and final risk notes.

Install

Implement frontend UI components from DESIGN.md, mockups, or screenshots with strict adherence to existing component system and accessibility.

Install

Frontend UI review for React, Next.js, Tailwind, accessibility, responsive layout, state handling, and component architecture.

Install

Git commit and pull request summary workflow using Conventional Commits and evidence from the current diff.

Install

Industrial automation and feedback-control inspired review for AI workflows, agents, orchestration loops, state machines, and reliability.

Install

Read-only planning workflow before implementation. Use for architecture, refactor, feature development, risky edits, and ambiguous tasks.

Install

Project-level operating rules extracted from AGENTS.md, DESIGN.md, and .omk/memory/. Apply silently before implementation.

Install

Python typed development standards using type hints, pytest, ruff, pyright, uv, and maintainable package structure.

Install

Run lint, typecheck, test, and build gates before completing any implementation task.

Install

Efficient repository exploration without dumping the whole codebase. Use before feature work, debugging, refactoring, and review.

Install

Web research and source verification workflow for current technical facts, libraries, APIs, pricing, policies, and documentation.

Install
Use cases

MCP Servers overview

README preview not available. Visit the repo on GitHub for full documentation.
agent-orchestrationagent-runtimeai-codingclaude-codeclicode-reviewcodexcoding-agentdeveloper-toolsdevtoolsevidencelocal-firstlocal-llmmcpmodel-context-protocolmulti-agentopencodesoftware-engineeringtypescriptworkflow-automation

What people ask about open-multi-agent-kit

What is dmae97/open-multi-agent-kit?

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dmae97/open-multi-agent-kit is mcp servers for the Claude AI ecosystem. Evidence-gated runner for Codex, Claude Code, OpenCode, and local coding agents. Routes tasks into scoped DAG lanes with replayable artifacts. It has 84 GitHub stars and was last updated today.

How do I install open-multi-agent-kit?

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You can install open-multi-agent-kit by cloning the repository (https://github.com/dmae97/open-multi-agent-kit) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is dmae97/open-multi-agent-kit safe to use?

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Our security agent has analyzed dmae97/open-multi-agent-kit and assigned a Trust Score of 87/100 (tier: Trusted). See the full breakdown of passed checks and flags on this page.

Who maintains dmae97/open-multi-agent-kit?

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dmae97/open-multi-agent-kit is maintained by dmae97. The last recorded GitHub activity is from today, with 14 open issues.

Are there alternatives to open-multi-agent-kit?

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Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

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