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CSOAI-ORG

API Tester AI MCP

by CSOAI-ORG
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

validate_response

Validate an API response by checking status code, body content, and required fields against expected values.

Instructions

Validate an API response against expectations.

Behavior: This tool is read-only and stateless — it produces analysis output without modifying any external systems, databases, or files. Safe to call repeatedly with identical inputs (idempotent). Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: status_code (int): The status code to analyze or process. body (str): The body to analyze or process. expected_status (int): The expected status to analyze or process. required_fields (str): The required fields to analyze or process. content_type (str): The content type to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
api_keyNo
status_codeYes
content_typeNo
expected_statusNo
required_fieldsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A3.7/5.0
Behavior5/5

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

Thoroughly covers all behavioral aspects: read-only, stateless, idempotent, rate limits, authentication, error handling, and data privacy. Since no annotations are provided, the description fully carries the burden and does so excellently.

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

Conciseness3/5

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

Well-structured with clear sections and front-loaded purpose, but there is significant redundancy between the 'Behavior' and 'Behavioral Transparency' sections. The 'Args' section is verbose without adding value.

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

Completeness3/5

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

Provides extensive behavioral context but is vague about the 'expectations' or 'frameworks' used for validation. Parameter meanings are under-explained. Output schema exists, so return values are not required, but overall completeness is average.

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

Parameters2/5

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

Schema coverage is 0%, but the 'Args' section provides only generic, repetitive descriptions like 'The status code to analyze or process,' adding no meaningful semantics beyond parameter names. The main description offers some context, but insufficiently.

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

Purpose4/5

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

The description clearly states the tool validates API responses against expectations, using specific verbs and resources. It implicitly distinguishes from siblings like 'send_request' and 'check_headers' by focusing on validation, but does not explicitly differentiate.

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?

Explicit 'When to use' and 'When NOT to use' sections provide clear guidance on appropriate contexts, including a caution against real-time production use without human review. However, it does not directly compare to sibling tools.

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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