SquadRules MCP
OfficialOptional Keycloak authentication integration, supporting browser sessions and Bearer JWT validation for the server's HTTP, API, and UI endpoints.
Provides an Ollama/OpenAI-compatible embedding backend for local or self-hosted embedding generation, used for protocol and adapter matching.
Provides an OpenAI embedding backend for the adapter store, enabling embedding generation for protocol and adapter matching and retrieval.
Optional Redis-backed cache and proof-of-work state storage, enabled when REDIS_URL is configured.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@SquadRules MCPactivate my create PR protocol and walk me through each step"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SquadRules
Help your AI remember how you like things done.
SquadRules gives AI assistants a shared place to keep your preferences and your team's ways of working. Instead of explaining the same things in every chat, your AI can find that knowledge and keep it up to date as your needs change. Even you and one AI assistant are a team.
Your AI does the work of maintaining this knowledge, so you do not have to manage it yourself.
Your AI owns the work
SquadRules is built for AI ownership and full autonomy by default:
Your AI creates, repairs, and maintains the workflows — called adapters — that carry your preferences. No human approval gates stand in the way.
Adapters run end to end. Each one finishes with a verification contract that checks real evidence — an observed file, a command result, or a reviewer's finding — instead of a claim that the work was done.
Your AI asks you only when a decision or permission is genuinely missing. Human input is an emergency path, not a routine confirmation step.
Details: adapter design principles and the adapter authoring guide.
Related MCP server: synapse-layer
Manual installation
You need Node.js 24 or newer and an AI app that supports MCP, the connection that lets your AI use SquadRules.
1. Connect SquadRules
Add this to your AI app's MCP configuration:
{
"mcpServers": {
"squadrules": {
"command": "npx",
"args": [
"-y",
"@squadrules/mcp@latest"
]
}
}
}Restart the app if it asks you to. The first start may take a little longer while SquadRules downloads what it needs.
2. Add the skill
The skill tells your AI when to use SquadRules. Run this in a terminal and follow the prompts to select your AI app:
npx skills add SquadRules/mcp --skill squadrulesUse an app that supports both MCP and skills. If you are unsure where to add the configuration or run the command, ask your AI assistant to help you set up SquadRules for your app.
Try it
Let's build our first SquadRules flow together. Ask me what I do often, help me improve it, and save the flow for next time.
Contributing
See Contributing and our development principles.
License and trademark
The code is licensed under MIT. The SquadRules name and logo are covered separately by TRADEMARK.md.
This server cannot be deployed
Maintenance
Related MCP Connectors
Governed local-first memory and continuity for AI agents — signed receipts, optional hosted lane.
Verified memory for AI agents. Signed assertions, billing attestation, session continuity.
Persistent agent memory paid per call via x402 USDC. Your wallet is your private memory namespace.
AI agent infrastructure for discovery, authorization, execution, identity, and signed receipts.
Related MCP Servers
- AlicenseNot gradedqualityAmaintenanceEnables AI agents to store and execute reusable protocol chains with persistent memory and deterministic execution.17 npm1MIT

synapse-layerofficial
AlicenseBqualityAmaintenanceMCP-native persistent memory for AI agents. Stores and retrieves encrypted memories with Trust Quotient scoring, cross-agent handover protocol, and immutable audit trail. 13 tools. Remote endpoint available.1331 PyPI13Apache 2.0- AlicenseNot gradedqualityBmaintenanceEnables AI agents to store, search, assemble, and manage local-first memories through seven MCP tools, including conversation turns, feedback, status, and dashboard access without cloud dependencies.AGPL 3.0
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to store and recall an append-only, hash-chained memory with citation-backed semantic search, fact verification, contradiction detection, and replay/audit capabilities through local MCP tools.1AGPL 3.0