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Execute SOPs step by step with enforced completion and auditability.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "sop-mcp" yet — see the docs or source repo.
Use sop-mcp to process a customer ticket step by step: 1) identify the issue type; 2) check the knowledge base; 3) draft a reply; 4) wait for my confirmation before sending. Pause after each step and report the result.
Ticket handling completed step by step, with clear results and confirmation at each stage.
Use sop-mcp to run the pre-launch SOP: 1) check configuration; 2) verify the environment; 3) run regression tests; 4) provide a release recommendation. Each step must be completed before moving on.
An auditable release checklist process and final recommendation.
Use sop-mcp to verify this dataset by SOP: 1) read the data; 2) check missing values; 3) flag anomalies; 4) summarize the verification results. Stop after each step and wait for the next instruction.
Stepwise verification results and an anomaly summary.
Establish engineering governance for AI software projects with traceable, auditable workflows.
Guide agents through structured workflows with flexible step execution and tool calls.
Build AI agent workflows and automate tasks using MCP-connected services.
Combine structured reasoning and execution so agents can think, act, and trace decisions.
Access StepFun text, vision, image, and speech models through MCP.
Run AI agents through OpenAI-compatible APIs with memory and multi-step workflows.