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.
npx agentmods add rules/vishnu2kmohan/mcp-server-langgraph/cursorrulesgit clone --depth 1 https://github.com/vishnu2kmohan/mcp-server-langgraphWhat 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 | $0.02038 | $0.02038 |
| Opus 5 | $0.01019 | $0.01019 |
| Sonnet 5 | $0.00408 | $0.00408 |
| Haiku 4.5 | $0.00204 | $0.00204 |
Grade A, and why
cursorrules 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 2d 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 — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cursor AI Rules for LangGraph MCP Agent
Project Overview
This is a production-ready LangGraph agent with Model Context Protocol (MCP) implementation, featuring:
- Multi-LLM support via LiteLLM (100+ providers)
- Fine-grained authorization with OpenFGA
- Secrets management with Infisical
- OpenTelemetry observability
- Kubernetes-ready deployment
Code Style Guidelines
Python
- Line length: 127 characters (enforced by black)
- Formatter: black with
--line-length=127 - Import sorting: isort with
--profile=black - Type hints: Always use type hints for function signatures
- Docstrings: Use Google-style docstrings
- Naming conventions:
- Classes: PascalCase
- Functions/methods: snake_case
- Constants: UPPER_SNAKE_CASE
- Private methods: _leading_underscore
File Organization
- Keep files focused and under 500 lines when possible
- Group related functionality together
- Use clear, descriptive file names
Architecture Patterns
Agent Design
- Use LangGraph's functional API for stateless operations
- Implement proper state management with checkpointing
- Keep agent logic separate from transport layer (MCP)
Authentication & Authorization
- Always validate JWT tokens before processing requests
- Use OpenFGA for fine-grained authorization checks
- Never hardcode credentials or secrets
- Use Infisical or environment variables for secrets
Error Handling
- Use specific exception types
- Log errors with trace context
- Return user-friendly error messages
- Never expose internal stack traces to clients
Observability
- Add OpenTelemetry spans for all major operations
- Use structured logging with context
- Track metrics for performance-critical paths
- Include trace IDs in all logs
Testing Guidelines
Test Structure
- Unit tests: Mark with
@pytest.mark.unit - Integration tests: Mark with
@pytest.mark.integration - E2E tests: Mark with
@pytest.mark.e2e - Benchmarks: Mark with
@pytest.mark.benchmark
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.
- 2d ago First seen · 358 lines · 2,038 tokens per session scan A fe8fa8d4d510
cursorrules is a cursor rule published in the GitHub repository vishnu2kmohan/mcp-server-langgraph (4 stars, last pushed 9d ago), licensed MIT. It adds 2,038 tokens to every session, about $0.0102 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 2026-08-31.
Other cursor rules, from other repositories
cursorrules
MCPCAN is a centralized management platform for MCP services. It deploys each MCP service using a container deployment method. The platform supports container monitoring and MCP service token verification, solving security risks and enabling rapid deployment of MCP services. It uses SSE, STDIO, and STREAMABLEHTTP…
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
cli-error-handling
CLI command error handling patterns.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.
control-plane-descriptors
Control plane descriptor and instance implementation patterns.