Access Analyzer MCP Server Integration Guide
Section A: Quick Answer & Architectural Summary
The Access Analyzer Model Context Protocol (MCP) integration bridges AI coding assistants to the Access Analyzer cloud infrastructure API. It exposes 10 validated endpoint operations as callable tools for Claude Desktop, Cursor, and VS Code. Configuration is managed via hosted registry at /config/amazonaws-com-accessanalyzer.json or local stdio bridge execution. Operates with zero authentication credentials out of the box. Contains 6 mutating operations (POST/PUT/DELETE); user confirmation is recommended before triggering write operations.
MCPBridge Editorial Verdict: Access Analyzer
AI coding workflows requiring programmatic access to Access Analyzer (Cloud Infrastructure) endpoints
Low (1-2 mins)
Zero Authentication Required
Automated Spec Tracking
Claude Desktop, Cursor IDE, VS Code (Cline), Zed Editor
Read & Mutating endpoints; client confirmation and least-privilege token recommended
MCPBridge rates Access Analyzer as a standardized OpenAPI-to-MCP bridge providing structured tool definitions across 10 endpoints.
Technical Overview & Protocol Integration
The AWS Identity and Access Management Access Analyzer API provides a powerful, policy-as-code service that automatically identifies resources accessible from outside your AWS account or organization. At its core, the service continuously evaluates resource-based policies—such as Amazon S3 bucket policies, AWS Identity and Access Management (IAM) roles, Amazon KMS key policies, and AWS Lambda function policies—using logic-based reasoning to determine which resources grant access to unknown external principals. Its primary use case is for security and compliance teams within enterprises to proactively detect unintended data exposure, enforce least privilege principles, and audit cross-account and cross-service access. The API endpoints allow programmatic control to create, configure, and query analyzers, manage archive rules for storing findings, and generate custom policy documents, making it a foundational tool for automating cloud security posture management at scale.
When exposed as tools through the Model Context Protocol (MCP) to an AI coding assistant like Claude Desktop or Cursor, the Access Analyzer API transforms from a cloud management tool into a dynamic, conversational security consultant for developers. The AI agent gains the ability to directly interact with the analyzer's intelligence layer, enabling a workflow where a developer can ask natural language questions like, "Analyze my S3 bucket named 'customer-data' for any public access risks," and the AI can orchestrate the appropriate API calls to fetch and interpret the latest findings. This integration significantly lowers the barrier to entry for complex security analysis, allowing developers without deep IAM expertise to get actionable insights within their IDE. The AI can also assist in policy remediation by using the policy generation endpoints to draft least-privilege policies based on the access patterns identified by the analyzer.
Practical workflows enabled by this MCP server include continuous security auditing and automated policy refinement. A developer can instruct the AI agent to perform tasks such as: "Query all active analyzers and summarize the most critical high-severity findings from the last 24 hours," or "Create a new analyzer for my organization's member accounts and configure an archive rule to store resolved findings in this S3 bucket." The AI can further automate lifecycle management by saying, "Review the findings for IAM roles created by CloudFormation in the dev environment and use the policy generation tool to propose a tightened policy that only allows the necessary API actions based on observed usage." This creates a powerful feedback loop where the AI acts as an intermediary between the developer's intent and the service's analytical capabilities, enabling proactive security hardening and drift detection without manual console navigation.
Critical security practices must be paramount when configuring this server. Although the API itself may use various authentication mechanisms, granting an AI agent access to these powerful tools requires strict adherence to the principle of least privilege. The IAM role or user credentials provided to the MCP server should have a minimal, scoped-down permission set, ideally restricted to read-only access to specific analyzer resources and the necessary findings reporting actions. Developers should avoid providing broad administrative permissions. It is essential to use managed policies or create custom policies that only allow actions like accessanalyzer:GetAnalyzer, accessanalyzer:ListFindings, and accessanalyzer:ListAnalyzers. Furthermore, sensitive analysis should be confined to designated accounts or regions, and all AI-agent-driven actions should be logged and monitored through AWS CloudTrail to maintain a clear audit trail of automated interactions with this critical security service.
By translating the OpenAPI 3.0 specification for Access Analyzer into native Model Context Protocol (MCP) tool definitions, developers and AI agents gain programmatic access to endpoints over stdio or HTTP transports. Every endpoint is translated into a discrete tool payload complete with input argument validation, parameter descriptions, and return type definitions.
2. Technical Specifications Matrix
System Specifications
| API Name | Access Analyzer |
| Slug Identifier | amazonaws-com-accessanalyzer |
| Category | Cloud Infrastructure |
| Auth Method | None Required |
| Endpoint Count | 10 tools mapped |
| Spec Version | OpenAPI v2019-11-01 |
| Transport Type | STDIO |
| Publisher Source | auto |
3. Multi-Client Installation Matrix
Copy and paste these pre-formatted JSON snippets into your MCP client configuration files.
Claude Desktop
Add to claude_desktop_config.json
{
"mcpServers": {
"amazonaws-com-accessanalyzer": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-openapi",
"https://api.apis.guru/v2/specs/amazonaws.com/accessanalyzer/2019-11-01/openapi.json"
],
"env": {
"ACCESS_ANALYZER_API_KEY": "your_access_analyzer_api_key"
}
}
}
}Cursor IDE
Settings → MCP Servers → Add Hosted Config
{
"mcpServers": {
"amazonaws-com-accessanalyzer": {
"url": "https://mcpbridge.org/config/amazonaws-com-accessanalyzer.json"
}
}
}Saves as .cursor/mcp.json in the download. Move it to your project root.
VS Code / Cline
Use with MCP extension config
{
"mcpServers": {
"amazonaws-com-accessanalyzer": {
"url": "https://mcpbridge.org/config/amazonaws-com-accessanalyzer.json"
}
}
}4. Security Architecture & Credentials Reference
Key parameters and credential variable mappings for Access Analyzer.
Security Considerations & Sandbox Guidance: Access Analyzer
Authorization credential isolation, least privilege boundaries, and container sandboxing options.
None Required
Read & Mutating Operations
Local MCP bridge process making outbound HTTPS requests to upstream API
Isolation & Principle of Least Privilege
Ensure outbound network access to the API endpoint is permitted. Use restricted API tokens with minimal read/write scopes.
Actionable Operational Guidelines
- Verify network firewall rules allow outbound traffic to upstream API endpoints.
- Review arguments for mutating endpoints (/archive-rule, /policy/generation/{jobId}, /access-preview) before execution.
- Apply token rate limits and monitor usage in your provider dashboard to prevent unexpected quota consumption.
| Variable Name | Required | Example Value |
|---|---|---|
| ACCESS_ANALYZER_API_KEY | REQUIRED | your_access_analyzer_api_key |
5. Endpoints & Tool Schemas Matrix
Search and inspect the 10 tool signatures mapped from OpenAPI.
Executable Code Integration Examples
Call Access Analyzer endpoints via cURL, TypeScript, or Python REST SDKs.
curl -X PUT "https://api.apis.guru/v2/specs/amazonaws.com/accessanalyzer/2019-11-01/archive-rule" \ -H "Content-Type: application/json" \ # No auth required
Concrete Real-World Use Cases for Access Analyzer
Practical multi-step agentic workflows and prompt directives demonstrating concrete developer outcomes.
Automated Contextual Workflow Integration
Practical workflows enabled by this MCP server include continuous security auditing and automated policy refinement. A developer can instruct the AI agent to perform tasks such as: "Query all active analyzers and summarize the most critical high-severity findings from the last 24 hours," or "Create a new analyzer for my organization's member accounts and configure an archive rule to store resolved findings in this S3 bucket." The AI can further automate lifecycle management by saying, "Review the findings for IAM roles created by CloudFormation in the dev environment and use the policy generation tool to propose a tightened policy that only allows the necessary API actions based on observed usage." This creates a powerful feedback loop where the AI acts as an intermediary between the developer's intent and the service's analytical capabilities, enabling proactive security hardening and drift detection without manual console navigation.
- AI assistant inspects prompt context and selects relevant tool
- Validates parameter payload against OpenAPI JSON Schema
- Executes tool call and formats structured API response
Data Inspection & Resource Querying
Query Access Analyzer resources such as "/policy/generation/{jobId}" to retrieve contextual data directly during coding sessions.
- Agent selects /policy/generation/{jobId} tool
- Passes search filters or resource identifiers
- Renders JSON payload in chat context for developer review
Automated Mutation & Resource Creation
Execute state changes and create records through PUT operations like "/archive-rule" with parameter validation.
- Agent constructs validated request body matching schema
- Prompts user for execution confirmation
- Executes tool and confirms response status
Good Fit vs. Poor Fit Criteria for Access Analyzer
Architectural guidelines to determine when to adopt this integration and when to explore alternatives.
When to Choose / Good Fit
- AI coding assistants in Claude Desktop or Cursor requiring structured tool access to Access Analyzer.
- Developers who want standardized OpenAPI-to-MCP translation without building custom server code.
- Workflows that benefit from automated parameter validation against official OpenAPI 3.0 schemas.
- Teams seeking zero-maintenance hosted JSON configurations for easy distribution.
When to Avoid / Poor Fit
- Ultra-high frequency data ingestion exceeding typical LLM context windows and token rate limits.
- Unattended autonomous agent loops with write access where human approval of mutations is mandatory.
- Environments lacking outbound internet access to upstream Access Analyzer API servers.
Verification & Evidence Audit: Access Analyzer
OpenAPI 3.0 specification parsed and validated via automated build pipeline.
Independent Evidence Checks
Valid specification version 2019-11-01 with 10 endpoints indexed.
No authentication required.
JSON Schemas mapped to MCP tools/call standard format.
Automated schema validation only; live upstream API calls require developer credentials.
Project Health & Maintenance Audit: Access Analyzer
ActiveActivity & Cadence
Transparent Quality Score Breakdown
Alternatives & Comparison Table (Cloud Infrastructure)
Comparative trade-offs between Access Analyzer and similar ecosystem tools in the Cloud Infrastructure category.
| Option | Best For | Main Difference vs. Access Analyzer | Setup / Runtime | Explore |
|---|---|---|---|---|
| ADHybridHealthService | Developers needing Cloud Infrastructure operations with 10 tools | 10 endpoints vs 10 endpoints | auto / v2014-01-01 | View → |
| AdvisorManagementClient | Developers needing Cloud Infrastructure operations with 9 tools | 9 endpoints vs 10 endpoints | auto / v2016-07-12-preview | View → |
| Amazon API Gateway | Developers needing Cloud Infrastructure operations with 10 tools | 10 endpoints vs 10 endpoints | auto / v2015-07-09 | View → |
9. Error Resolution & Troubleshooting Guide
Contextual diagnostics for HTTP status codes and JSON-RPC tool bridge operations.
-32600 (Invalid Request)Root Cause: Malformed JSON-RPC payload sent to local MCP bridge process.
Resolution Action: Verify MCP client payload adheres to JSON-RPC 2.0 specification.
-32601 (Method Not Found)Root Cause: Requested operation does not exist in mapped Access Analyzer OpenAPI endpoint schemas.
Resolution Action: Inspect Section 5 endpoints table to confirm valid method names and paths.
-32602 (Invalid Params)Root Cause: Missing or invalid parameters for target tool operation.
Resolution Action: Check parameter data types against OpenAPI JSON Schema specification.
429 Rate Limit ExceededRoot Cause: Upstream Access Analyzer API request rate limit quota reached.
Resolution Action: Implement exponential backoff in tool execution loop or verify provider plan quotas.
OPENAPI_GATEWAY_TIMEOUTRoot Cause: Upstream Access Analyzer endpoint response latency exceeded timeout threshold.
Resolution Action: Verify network connectivity and check provider system status dashboard.
Official Verified Sources for Access Analyzer
Authoritative upstream repositories, specifications, package registries, and configuration endpoints.
Official Upstream Documentation
Official developer documentation and API reference for Access Analyzer.
https://docs.aws.amazon.com/access-analyzer/OpenAPI 3.0 Specification
Machine-readable OpenAPI schema source used for MCP tool mapping.
https://api.apis.guru/v2/specs/amazonaws.com/accessanalyzer/2019-11-01/openapi.jsonHosted MCPBridge Configuration
Pre-generated Model Context Protocol JSON configuration hosted on MCPBridge.
https://mcpbridge.org/config/amazonaws-com-accessanalyzer.jsonOpenAPI-to-MCP Converter Tool
Client-side browser converter to customize or filter endpoint tools.
https://mcpbridge.org/convert/Claim & Maintainer Verification
Submit a claim to verify API publisher ownership and update metadata.
https://github.com/stormlive-ai/mcp-bridge-docs/issues/new?title=Claim+Listing%3A+Access+Analyzer+%28api%3A+amazonaws-com-accessanalyzer%29&labels=claim-listing&body=%23%23+Claim+Listing+Request%0A%0AI+would+like+to+claim+this+listing%3A%0A%0A-+**Type%3A**+api%0A-+**ID%3A**+amazonaws-com-accessanalyzer%0A-+**Name%3A**+Access+Analyzer%0A%0A%23%23%23+Your+Information%0A%0A**GitHub+Handle%3A**+%3C%21--+your+GitHub+username+--%3E%0A%0A**Email%3A**+%3C%21--+optional%2C+for+verification+--%3E%0A%0A**Relationship+to+this+API%3A**%0A-+%5B+%5D+I+am+the+API+provider+%2F+maintainer%0A-+%5B+%5D+I+am+an+authorized+representative%0A-+%5B+%5D+Other%3A%0A%0A%23%23%23+Verification+Method%0A-+%5B+%5D+I+will+add+a+CNAME%2FTXT+record+to+verify+domain+ownership%0A-+%5B+%5D+I+can+confirm+from+an+email+address+at+the+provider+domain%0A-+%5B+%5D+I+maintain+the+GitHub+repository%0A%0A%23%23%23+Updates+I%27d+Like+to+Make+%28optional%29%0A%3C%21--+What+would+you+like+to+update%3F+Description%2C+links%2C+category%2C+etc.+--%3E%0A%0A---%0A*Submitted+via+MCP-Bridge+claim+form*Frequently Asked Technical Questions: Access Analyzer
Targeted developer questions regarding installation, client configuration, credentials, and error resolution.
The Access Analyzer MCP server connects AI coding assistants (Claude Desktop, Cursor, VS Code, Zed) to the Access Analyzer API using the Model Context Protocol. It converts 10 OpenAPI operations into native MCP tools callable during chat sessions.