Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Matt-Dionis/claude-code-configsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/matt-dionis/claude-code-configs/setup)<a href="https://agentmods.dev/commands/matt-dionis/claude-code-configs/setup"><img src="https://agentmods.dev/badge/commands/matt-dionis/claude-code-configs/setup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/matt-dionis/claude-code-configs/setup"><img src="https://agentmods.dev/badge/commands/matt-dionis/claude-code-configs/setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00007 | $0.02630 |
| Opus 5.5 | $0.00003 | $0.01052 |
| Sonnet 5.5 | $0.00001 | $0.00526 |
| Haiku 4.5 | $0.00001 | $0.00263 |
Grade A, and why
setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 382 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory MCP Server Setup
Initialize and configure the Memory MCP Server project based on $ARGUMENTS:
Quick Setup
Initialize minimal working MCP server with memory capabilities:
# Initialize project
npm init -y
npm install @modelcontextprotocol/sdk zod dotenv
npm install -D typescript @types/node tsx nodemon
npm install @neondatabase/serverless drizzle-orm@^0.44.4
npm install openai pgvector
# Create TypeScript config
npx tsc --init
Full Setup
Complete project initialization with all features:
1. Project Structure
memory-mcp-server/
├── src/
│ ├── index.ts # MCP server entry point
│ ├── server.ts # Server initialization
│ ├── tools/ # MCP tool implementations
│ │ ├── createMemory.ts
│ │ ├── searchMemories.ts
│ │ ├── getMemory.ts
│ │ ├── updateMemory.ts
│ │ └── deleteMemory.ts
│ ├── db/
│ │ ├── client.ts # Database connection
│ │ ├── schema.ts # Drizzle schema
│ │ └── migrations/ # Database migrations
│ ├── services/
│ │ ├── embeddings.ts # OpenAI embeddings
│ │ ├── vectorSearch.ts # pgvector operations
│ │ └── memoryLifecycle.ts # Memory management
│ ├── types/
│ │ └── index.ts # TypeScript types
│ └── utils/
│ ├── logger.ts # Structured logging
│ └── errors.ts # Error handling
├── tests/
│ ├── unit/
│ ├── integration/
│ └── fixtures/
├── .env.example
├── .mcp.json # MCP manifest
├── tsconfig.json
├── package.json
├── drizzle.config.ts
└── README.md
2. Package Dependencies
{
"name": "memory-mcp-server",
"version": "1.0.0",
"type": "module",
"scripts": {
"dev": "tsx watch src/index.ts",
"build": "tsc",
"start": "node dist/index.js",
"test": "jest",
"test:watch": "jest --watch",
"test:coverage": "jest --coverage",
"lint": "eslint . --ext .ts",
"typecheck": "tsc --noEmit",
"db:generate": "drizzle-kit generate",
"db:migrate": "drizzle-kit migrate",
"db:studio": "drizzle-kit studio"
},
"dependencies": {
"@modelcontextprotocol/sdk": "^1.0.0",
"@neondatabase/serverless": "^1.0.1",
"drizzle-orm": "^0.44.4",
"zod": "^4.0.17",
"openai": "^4.0.0",
"pgvector": "^0.2.0",
"dotenv": "^16.0.0",
"winston": "^3.0.0"
},
"devDependencies": {
"@types/node": "^20.0.0",
"typescript": "^5.0.0",
"tsx": "^4.0.0",
"nodemon": "^3.0.0",
"jest": "^29.0.0",
"@types/jest": "^29.0.0",
"ts-jest": "^29.0.0",
"eslint": "^8.0.0",
"@typescript-eslint/eslint-plugin": "^6.0.0",
"@typescript-eslint/parser": "^6.0.0",
"drizzle-kit": "^0.32.0"
}
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 382 lines · 7 tokens per session scan A d4b488109322
setup is a command published in the GitHub repository Matt-Dionis/claude-code-configs (619 stars, last pushed 1y ago), licensed MIT. It adds 7 tokens to every session and 2,630 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.