sample-sop-mcp
Turn repeatable processes into SOPs your AI agent works through one auditable step at a time.
Install / Use
claude mcp add aws-samples -- npx -y github:aws-samples/sample-sop-mcpIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of sample-sop-mcp
sample-sop-mcp scores 81/100 on our quality scale, 723rd of 928 AI & Machine Learning skills we index.
Its MCP Server is 13 KB long, well organised into 17 sections with 4 code examples: a thorough specification that gives an agent plenty to work with.
It has 10 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated today, so sample-sop-mcp is actively maintained.
- It is released under the MIT-0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 92/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-10-29. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
sample-sop-mcp compared with similar skills
All 4 of these similar skills score higher than sample-sop-mcp; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| sample-sop-mcp (this skill)by aws-samples | 81 | 10 | today | MCP Server |
| Agent-Reachby Panniantong | 100 | 105.7k | 4d ago | CLAUDE.md |
| claude-memby thedotmack | 100 | 104.1k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 88.8k | 3d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 78.2k | today | CLAUDE.md |
Frequently asked questions
- How do I install sample-sop-mcp?
- Run
claude mcp add aws-samples -- npx -y github:aws-samples/sample-sop-mcp. The install tabs above show the steps for each supported agent. - Which AI agents does sample-sop-mcp work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is sample-sop-mcp safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-0-licensed and scores 92/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is sample-sop-mcp still maintained?
- The repository was last updated today, so sample-sop-mcp is actively maintained.
Skill content
View source on GitHubsample-sop-mcp
Turn your repeatable processes into Standard Operating Procedures (SOPs) that an AI agent executes one step at a time.
An MCP server that hands a procedure to your AI assistant one step at a time and asks it to produce concrete output before moving on. You talk to your agent in plain language — Kiro, Cursor, Claude Desktop, a Strands agent, or any MCP client — and it calls the SOP tools for you under the hood.
✨ Features
- 🗣️ Plain-language driven — Ask your agent to run or author an SOP; you never call tools by hand
- 👣 Step-at-a-time execution — Each step must be executed and produce output before the agent advances
- ✅ Gated & auditable — RFC 2119 levels (MUST, SHOULD, MAY) delivered one step at a time, each gated behind the previous, with progress kept explicit
- 📦 Batteries included — Four ready-to-run SOPs seeded on first launch
- ✍️ Guided authoring — A built-in guide interviews you, drafts, lints, and publishes new SOPs
- 🔌 Works everywhere — One-click install for Kiro, Cursor, and VS Code; manual config for any MCP client
🤔 What's an SOP?
A Standard Operating Procedure is a markdown document that captures a repeatable, multi-step process — a code review, onboarding a new hire, cutting a release. LLMs are powerful but unpredictable across multi-step work: they skip steps, summarize instead of act, and lose their place. sop-mcp makes that behavior predictable — procedures arrive step by step, execution is gated, and progress is explicit.
<p align="center"> <img src="docs/banner.svg" alt="sop-mcp" width="100%"> </p>🚀 Quick Start
1. Install
Add the server with one click, or paste the config below.
| Kiro | Cursor | VS Code |
| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| |
|
|
{
"mcpServers": {
"sop-mcp": {
"command": "uvx",
"args": ["--from", "git+https://github.com/aws-samples/sample-sop-mcp", "sop-mcp"]
}
}
}
uvx fetches and runs the server straight from this repo — no clone or build. On first run it seeds four bundled SOPs into your storage directory. SOP_STORAGE_DIR is optional (see Storage).
2. Verify the install
Restart your MCP client, then ask your agent to list the available SOPs:
You: "List available SOPs."
You should see the bundled SOPs — sop_creation_guide, code_review_process and more. If none appear, check your MCP client's server logs for errors.
3. Run an SOP
Just ask your agent. It discovers the available SOPs, starts the one you named, and walks through it step by step — doing the work each step describes before advancing.
You: "Run the code review SOP for my current branch."
You stay in the conversation: review each step's output, answer questions, or course-correct as it goes.
4. Author an SOP
Ask the agent to run the built-in authoring guide. It interviews you, drafts the SOP, validates it against the linter, and publishes it — all through conversation.
You: "Help me write a new SOP for our release process — use the sop_creation_guide."
You: "Looks good — publish it as preprod."
A clean lint means a clean publish, so your SOP is immediately runnable: "Run my_release_process."
🔄 How It Works
<p align="center"> <img src="docs/how-it-works.svg" alt="How sop-mcp works — a step-gated sequence" width="100%"> </p> <details> <summary>Same flow as a Mermaid sequence diagram</summary>sequenceDiagram
actor User
participant Agent as AI Agent (MCP client)
participant SOP as sop-mcp server
participant Store as SOP storage (~/.sop_mcp)
User->>Agent: "Run the code review SOP"
Agent->>SOP: list_resources
SOP->>Store: scan *.sop.md
Store-->>SOP: SOP names
SOP-->>Agent: available SOPs (sop://...)
Agent->>SOP: run_sop(sop_name, current_step=0)
SOP->>Store: read SOP markdown
SOP-->>Agent: Step 1 of N + execution rules
Agent->>Agent: execute step 1 (do the work)
Agent->>SOP: run_sop(current_step=1, step_output="...")
Note over Agent,SOP: required — step_output gates the next step
opt human in the loop
Agent-->>User: optionally show progress / ask input
end
SOP-->>Agent: Step 2 of N
Note over Agent,SOP: repeat until the final step
SOP-->>Agent: "SOP execution complete."
Agent-->>User: done
</details>
Each step tells the agent to execute — not just read. It must produce the step's expected output before advancing, which is what makes the run auditable. As the human in the loop, you see each step's result and can intervene at any point.
⚠️ Treat SOP content as untrusted. sop-mcp serves SOP markdown to your agent verbatim — it can't tell a legitimate instruction from a malicious one. If your
SOP_STORAGE_DIRis shared, synced, or holds SOPs you didn't author, review an SOP before running it: a crafted SOP could steer the agent into unintended actions (prompt injection). Keep a human in the loop for steps with real-world side effects.
🧩 Agent SOPs vs. Skills
The SOPs here use the Agent SOP format — portable markdown workflows (parameterized, with RFC 2119 MUST/SHOULD/MAY constraints) that guide an agent through a multi-step process. An Agent Skill is also markdown that guides an agent, so the two look similar — the real difference is how the instructions reach the agent:
- As a skill — the whole playbook loads into context at once and the agent self-directs, so it can read ahead, skip, batch, or summarize. Great for domain knowledge and flexible tasks. (Agent SOPs can even be exported to the Skills format.)
- Via sop-mcp — the same SOP is metered out one step at a time. The agent sees only the current step and must report its output before the next is released. It can't look ahead or skip — which is what makes a multi-step run consistent and auditable.
| | As a Skill | Run via sop-mcp | | ----------------- | -------------------------------- | -------------------------------------------------- | | Delivery | whole playbook at once | one step at a time | | Sequencing | agent self-discipline | gated — output required to advance | | Progress state | none | tracked and explicit | | Look ahead / skip | possible | not possible | | Form | static markdown file | running server + tools (lint / publish / feedback) | | Best for | domain reference, flexible tasks | multi-step processes needing consistency & audit |
(Separately, this repo also ships a regular skill — sop-mcp-usage — that teaches an agent how to drive the server.)
📦 Bundled SOPs
Four SOPs ship with the server — ask your agent to run any by name:
| SOP | What it does |
| --------------------------- | --------------------------------------------------------------------------- |
| sop_creation_guide | Guided 7-step walkthrough for authoring new SOPs with RFC 2119 requirements |
| code_review_process | Standard code review workflow — prepare, review, address feedback, merge |
| employee_onboarding_setup | IT setup for a new hire — alias, email, hardware selection |
| user_onboarding_process | Provision identity, application access, and welcome package |
🛠️ Tools
The agent calls these on your behalf — you won't invoke them directly.
| Tool | Purpose |
| --------------------- | -------------------------------------------------------------------------------------- |
| list_resources | Discover available SOPs (built in to every MCP client) |
| read_resource | Read an SOP's full content before executing it |
| run_sop | Execute an SOP step by step |
| lint_sop | Validate a draft SOP against the same rules publish_sop enforces, without writing it |
| publish_sop | Create or update an SOP |
| submit_sop_feedback | Record improvement suggestions |
Full parameter reference: docs/mcp-reference.md
💾 Storage
On first run the server seeds the bundled SOPs into your storage directory — ~/.sop_mcp by defaul
Truncated for display — read the full file on GitHub.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
