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sanyambassi

thales-cdsp-csm-mcp-server

by sanyambassi

get_api_reference

Generate production-ready code examples and integration patterns for Thales CipherTrust secrets management APIs, covering auth, secret creation, retrieval, and role management.

Instructions

API REFERENCE TOOL - Generate production-ready code examples and integration patterns

SUPPORTED ENDPOINTS: • workflow: Complete integration patterns and best practices • auth: Authentication flows and token management • create-secret: Secret creation and management APIs • get-secret-value: Secret retrieval and access patterns • list-items: Item listing and discovery APIs • delete-item: Item deletion and cleanup operations • list-roles: Role management and access control • list-targets: Target management and configuration

INTEGRATION FEATURES: • Production-ready code examples with authentication • Complete error handling and retry logic • Best practices for secure integration patterns • Multi-language support (Python, JavaScript, etc.) • Token management and session handling

USE CASES: • Building custom applications and integrations • CI/CD pipeline integration and automation • Microservice authentication and configuration • Native client development and SDK creation • Production system integration and deployment

Example: Generate complete Python client code for secret management

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoTarget programming language for code examples and implementation detailspython
api_endpointYesAPI endpoint or integration pattern to get reference for. SUPPORTED: 'workflow' (complete integration patterns), 'auth' (authentication flows), 'create-secret' (secret creation), 'get-secret-value' (secret retrieval), 'list-items' (item listing), 'delete-item' (item deletion), 'list-roles' (role management), 'list-targets' (target management)
include_authNoInclude complete authentication workflow and token management examples
include_error_handlingNoInclude production-ready error handling, retry logic, and exception management

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the transparency burden. It discloses several behavioral aspects: generates code with authentication, error handling, retry logic, token management, and multi-language support. It implies a read-only reference nature but does not explicitly state there are no side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections for supported endpoints, integration features, use cases, and an example. While somewhat verbose, every section serves a purpose and the content is organized with bullet points, making it easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the rich output schema and 100% parameter coverage, the description thoroughly covers purpose, supported endpoints, generated features, and usage scenarios. It is complete for an AI agent to understand how and when to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with detailed parameter descriptions for language, api_endpoint, include_auth, and include_error_handling. The tool description adds context by elaborating on endpoint-specific integration patterns, but this complements rather than significantly extends the schema. Baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: generate production-ready code examples and integration patterns. It lists supported endpoints and integration features, distinguishing it from sibling manage_* tools that handle resource management rather than API reference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a dedicated 'USE CASES' section with scenarios like building custom applications, CI/CD integration, microservice auth, and SDK development. It gives clear context for when to use the tool but does not explicitly state when not to use it or name alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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