awesome-cursor-rules-mdc is a generator that creates Cursor MDC rule files from structured library information, using semantic search and language models to gather and organize guidance. Developers use it to produce reusable rules for libraries in Cursor, and the catalogue includes 200 of those rules.
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/sanjeed5/awesome-cursor-rules-mdcWrote 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/rules/sanjeed5/awesome-cursor-rules-mdc/postman)<a href="https://agentmods.dev/rules/sanjeed5/awesome-cursor-rules-mdc/postman"><img src="https://agentmods.dev/badge/rules/sanjeed5/awesome-cursor-rules-mdc/postman.svg" alt="Measured on agentmods" 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 | $0.02838 | $0.02838 |
| Opus 5 | $0.01419 | $0.01419 |
| Sonnet 5 | $0.00568 | $0.00568 |
| Haiku 4.5 | $0.00284 | $0.00284 |
Grade A, and why
postman 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 3d 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 — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Postman Best Practices
Postman is our definitive tool for API development, testing, and documentation. Adhering to these guidelines ensures consistency, maintainability, and reliability across all our API interactions.
1. Code Organization and Structure
Organize your Postman collections like source code: structured, versioned, and modular.
1.1 Collection Hierarchy
Mirror your API's resource structure with a clear folder hierarchy. Each folder should represent a logical API resource or module.
❌ BAD: Flat Collection
- My API
- Create User
- Get User by ID
- Update Product
- Delete Order
✅ GOOD: Structured Collection
- My API v1.0
- Users
- POST Create User
- GET Get User by ID
- PUT Update User
- DELETE Delete User
- Products
- POST Create Product
- GET Get Product by ID
- PUT Update Product
- DELETE Delete Product
- Orders
- POST Create Order
- GET Get Order by ID
- PUT Update Order
- DELETE Delete Order
1.2 Request Naming
Use descriptive names for requests, including the HTTP method and the resource path.
❌ BAD: Vague Request Names
- Get User
- Update Product
✅ GOOD: Explicit Request Names
- GET /users/{id}
- PUT /products/{id}
- POST /auth/login
1.3 Variables Management
Leverage Postman variables (global, environment, collection) to avoid hardcoding and promote reusability.
- Global Variables: For non-sensitive, truly global data (e.g., common utility functions). Use sparingly.
- Environment Variables: For environment-specific configurations (e.g.,
BASE_URL,AUTH_TOKEN,API_KEY). Never commit sensitive data to source control. - Collection Variables: For data specific to a collection (e.g.,
user_id,product_name) that might change during a test run but is not environment-specific.
Naming Convention:
- Environment Variables:
UPPER_SNAKE_CASE(e.g.,DEV_BASE_URL,PROD_AUTH_TOKEN) - Collection/Local Variables:
camelCase(e.g.,userId,productName)
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.
- 3d ago First seen · 364 lines · 2,838 tokens per session scan A 8298bcf004b5
postman is a cursor rule published in the GitHub repository sanjeed5/awesome-cursor-rules-mdc (3,571 stars, last pushed 3mo ago), licensed CC0-1.0. It adds 2,838 tokens to every session, about $0.0142 per session on Opus 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 2026-09-03.
Other cursor rules, from other repositories
python_tests
We use the unit tests to cover internal behavior that can work without the web / backend counterpart. We aim for 95%+ unit test coverage of our Python code in lib/streamlit.
validate-contracts
Assert data shape consistency across system boundaries — live API responses against JSON Schema, key-set comparison across layers, data shape validation for migrations and exports. Catches silent data corruption before deploy.
manual-review.backend
A set of rules for verifying backend-only changes and changes that use different verification channels. It separates evidence the agent can collect from checks that require a person, a production authorization, or a business decision.
create-a-testable-http-client-service
Cursor rule "create-a-testable-http-client-service" from PaulJPhilp/EffectPatterns, covering create a testable http client service, example, 1. define the service, 2. create the live implementation and 3. create the test implementation.
architecture
This document outlines the fundamental architectural principles and patterns for the mcp-debug codebase. Adherence to these guidelines is mandatory to maintain a clean, decoupled, and testable system.
issues-tests
Backend test conventions — QuarkusTest, REST Assured, Given, ArchUnit.