OpenMesha
Related Servers
Alternatives to OpenMesha
No user-submitted related servers found.
Related Servers
- AlicenseBqualityCmaintenanceEnables MCP-compatible clients to manage AI agent teams, including agents, Kanban issues, projects, goals, approvals, budgets, and raw API access.30MIT
- AlicenseAqualityBmaintenanceEnables MCP-capable agents to create and invoke OpenServerless endpoints, manage secrets, and configure integrations such as S3, PostgreSQL, Redis, Milvus, and MongoDB.13Apache 2.0

meshive-mcpofficial
AlicenseNot gradedqualityAmaintenanceEnables MCP-capable agents to manage Meshive GPU Cloud resources, including account, workspaces, pods, storage, GPUs, templates, serverless deployments, tasks, assets, machines, and billing history.Apache 2.0- AlicenseNot gradedqualityAmaintenanceEnables AI agents to manage API keys and child keys with budgets and spending caps, set plans and model routing, handle wallet payments and top-ups, and verify signed receipts through MCP tools.265 npm2MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI clients to manage workspaces, projects, tasks, and AI agents through natural language, with hosted or local connection options and OpenAPI-to-MCP tool generation.1,264 npmMIT
- AlicenseNot gradedqualityDmaintenanceEnables multi-model leader-worker agent orchestration, workflow execution, and deterministic validation via structured MCP tools.6 npmApache 2.0
TDQS
Scored across 9 tools
Each tool targets a distinct action or resource: agent lifecycle, workflow creation, reporting, capability listing, and payment quoting are clearly separated. The get_cost_ledger, get_audit_log, and get_metrics tools explicitly disambiguate their boundaries in their descriptions.
Most tools follow a clear verb_noun pattern such as list_agents, create_agent, run_task, and get_metrics. The outlier is x402_payment_quote, which is a noun-phrase name with no leading verb, creating a minor inconsistency.
Nine tools is a well-scoped count for an agent orchestration and governance server. Each tool addresses a meaningful part of the workflow without feeling redundant or padded.
The core lifecycle of creating agents, listing agents, running tasks, and creating workflows is covered, along with cost, audit, and metrics reporting. Missing update/delete/stop agent operations are notable but not critically blocking for the apparent in-process simulation scope.