MCP Task Orchestrator
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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.
Stars
193
Δ stars 7d
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Δ stars 30d
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Forks
22
Contributors
2
npm DL / wk
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PyPI DL / wk
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Language
Kotlin
Last push
2026-06-01
About MCP Task Orchestrator
Prompt-based frameworks hope the LLM follows instructions. This one blocks the call if it doesn't. Multi-agent workflows need infrastructure the model doesn't provide. When an orchestrator dispatches sub-agents across sessions, there's no built-in way to enforce what documentation must exist before work starts, track which agent made which change, or guarantee dependency ordering across a work breakdown. These are structural concerns — they belong in the server, not in prompts. Task Orchestrator is an MCP server — not a prompt layer. It…
Read the full README on GitHub →
MCP Task Orchestrator alternatives
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Frequently asked questions
- Is MCP Task Orchestrator still maintained?
- Yes — actively maintained. The last push was on 2026-06-01, with 2 contributors.
- What are the best MCP Task Orchestrator alternatives?
- Closest by category and size in our data: io.github.SepineTam/stata-mcp, io.github.marianfoo/mcp-sap-docs, ai.smithery/zwldarren-akshare-one-mcp — full list with live signals above.
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Tracked since 2026-06-10 · data as of 2026-06-10 · 0 open issues · 23 releases