a coding Agent, rpc plugin, sub-agents, hashline edits, and mcp
Our agent harness: Skills, plugins, hooks, and utilities to improve the quality of your agent.
Build Your Agent Company with OMC

Agentic dev environment for DevPods, Codespaces & Rackspace Spot — one-command setup of Ruflo orchestration (215+ MCP tools, 60+ agents upstream).
Multi-agent orchestration for Claude Code with 15-30% token optimization, self-improving agents, and automatic verification
Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.
Unified AI Development Framework - BMAD phases with Ralph execution loop
One folder. Every session knows where you left off. — An open-source methodology for AI-assisted projects.
Prismer Cloud
Safe local execution layer for AI agent tools. Build, validate, and publish MCP tools with a no-pass-no-run workflow — cross-platform desktop app powered by Spring AI.
The orchestration layer under your coding agent. Turns work into a typed graph, runs one model per node, and takes the verdict from outside the model — exit codes, write-set checks, and a cross-family verifier. MCP server, 50 tools, bring your own models.
Mantis Hack
Local-first coordination for human and agent work: durable work, decisions, dispatches, evidence, and prompt-first methods, powered by TypeScript and Bun.
A workflow framework for statistical package development
Portable AI agent orchestration with mechanical protocol enforcement. 186 agents, zero runtime dependencies.
Build tested agent skills and govern their lifecycle through a user-defined marketplace: evidence, discovery, updates, rollback, quarantine, and 17-platform distribution.
Open-source AI agent harness in native Rust — GUI, CLI, headless, and webapp from one binary. Multi-provider, MCP, skills, plugins, agent teams.
MCP Server Security Standard (MSSS): an open, testable security control standard for certifying MCP servers, with levels, evidence requirements, and reporting schemas.
a recursive self-improving harness designed to help your agents (and future iterations of those agents) succeed on any task
SAW — SAFe Agentic Workflow AI Agent Harness for Multi-Agent Team Workflows Built on SAFe methodology (Scaled Agile Framework), adapted for AI agent teams (Now With AI-DLC!) Works for any team with repeatable processes: Software, Marketing, Research, Legal, Operations.
Give AI agents eyes, ears, and verifiable results. Watch Skill turns video, audio and screen activity into searchable, timestamped evidence and proves work with deterministic contracts, not model opinion. DeepWatch is the agent workspace built on DeepSeek Harness. Python + npm, MCP, CLI, REST, Web.
From thought to skill. From signal to structure.

The most RAM efficient harness

MCP Playbooks for AI agents