Borrowing it
Nothing to install: this file belongs to vishnu2kmohan/mcp-server-langgraph. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/vishnu2kmohan/mcp-server-langgraph/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/vishnu2kmohan/mcp-server-langgraphWrote 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/instructions/vishnu2kmohan/mcp-server-langgraph/copilot-instructions)<a href="https://agentmods.dev/instructions/vishnu2kmohan/mcp-server-langgraph/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/vishnu2kmohan/mcp-server-langgraph/copilot-instructions/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/instructions/vishnu2kmohan/mcp-server-langgraph/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/vishnu2kmohan/mcp-server-langgraph/copilot-instructions.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 | $0.02343 | $0.02343 |
| Opus 5.5 | $0.00937 | $0.00937 |
| Sonnet 5.5 | $0.00469 | $0.00469 |
| Haiku 4.5 | $0.00234 | $0.00234 |
Grade A, and why
mcp-server-langgraph copilot-instructions.md scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(url) How it starts
The opening of the file, as written. The whole thing — 405 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Copilot Instructions for MCP Server with LangGraph
Project Context
You are working on a production-ready LangGraph agent with Model Context Protocol (MCP) implementation. This is enterprise-grade software with:
- Multi-LLM Support: 100+ providers via LiteLLM
- Security: JWT auth + OpenFGA fine-grained authorization
- Secrets: Infisical integration
- Observability: OpenTelemetry (traces, metrics, logs)
- Deployment: Kubernetes with Helm/Kustomize
Code Style
Python Standards
- Black formatter: 127 character line length
- Type hints: Always required for public APIs
- Docstrings: Google-style for all public functions
- Import order: Standard → Third-party → Local (via isort)
# Example
def process_message(message: str, user_id: str) -> AgentResponse:
"""
Process a user message through the agent.
Args:
message: The user's input message
user_id: Unique user identifier
Returns:
AgentResponse with the agent's reply
Raises:
AuthorizationError: If user lacks permissions
"""
pass
Testing Standards
- Mark all tests:
@pytest.mark.unit,@pytest.mark.integration, etc. - Mock external services (LLMs, OpenFGA, Infisical)
- Aim for >80% coverage on critical paths
@pytest.mark.unit
def test_process_message_success():
"""Test message processing with valid input."""
# Arrange
message = "Hello, agent"
user_id = "user-123"
# Act
response = process_message(message, user_id)
# Assert
assert response.status == "success"
assert len(response.content) > 0
Security Requirements
Authentication
- Never hardcode secrets
- Use
settings.jwt_secret_keyfrom config - Validate tokens on every request
- Log all auth failures
# ✅ Good
token = settings.jwt_secret_key
# ❌ Bad
token = "hardcoded-secret"
Authorization
- Check OpenFGA before protected operations
- Use principle of least privilege
- Log authorization failures with context
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 · 405 lines · 2,343 tokens per session scan A b1cd7d693643
mcp-server-langgraph copilot-instructions.md is an instructions file published in the GitHub repository vishnu2kmohan/mcp-server-langgraph (4 stars, last pushed 2d ago), licensed MIT. It adds 2,343 tokens to every session, about $0.0094 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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