implementation

Develop Model Context Protocol (Model Context Protocol) Tool for IAM

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Graph-Based Identity Security Agent

Format

Text-first

Lines

Sections

Linked challenge

Graph-Based Identity Security Agent

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

1 sections

No variables

0 checklist items

Create a simulated enterprise Identity and Access Management (IAM) system API, and then build a Model Context Protocol (Model Context Protocol)-enabled tool that your LangGraph agent can call. This tool should allow the agent to 'simulate_revoke_access' or 'query_user_audit_logs'. Provide the Model Context Protocol schema and an example agent-side call.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.

Prompt diagnostics

Variables

Lists

Code blocks

Purpose

implementation

This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

Graph-Based Identity Security Agent

This challenge focuses on building an intelligent agent system capable of analyzing complex user, system, and access relationships to identify security risks. You will construct a knowledge graph representing an enterprise's identity landscape, then leverage Gemini 3 for advanced reasoning over this graph. Your primary task is to develop a graph-based agent workflow using LangGraph to traverse and query this knowledge graph. The agent will integrate with LlamaIndex for Retrieval-Augmented Generation (RAG) to fetch relevant context from the graph, and utilize MCP-enabled tools to interact with simulated enterprise identity systems (e.g., Active Directory, HR databases). The agent should be able to perform extended thinking with adaptive reasoning budgets to detect anomalous access patterns, privilege escalations, and provide risk assessments.

Open challenge

Related prompts

Browse library

Define Knowledge Graph Schema and Data

planning

Build LangGraph Workflow for Risk Analysis

implementation

Execute and Evaluate Risk Assessment

testing