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zebbern

Webhook.site MCP Server

by zebbern

search_requests

Search and filter webhook requests by method, content, headers, date range, or type to inspect captured HTTP, email, and DNS data.

Instructions

Search requests sent to a webhook with query filters (method, content, headers, date range, type).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
webhook_tokenYesThe webhook token (UUID) from webhook.site
request_typeNoFilter by request type: 'web' (HTTP requests), 'email', or 'dns'
queryNoAdditional search query (e.g., 'method:POST', 'content:foobar', 'headers.user-agent:Mozilla')
date_fromNoFilter from date (format: yyyy-MM-dd HH:mm:ss)
date_toNoFilter to date (format: yyyy-MM-dd HH:mm:ss)
sortingNoSort order: 'newest' or 'oldest'newest
limitNoMaximum number of requests to retrieve
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'search' but doesn't clarify if this is a read-only operation, whether it requires authentication, or how results are returned (e.g., pagination, format). The description lacks critical behavioral details like rate limits or error handling, leaving significant gaps for a tool with 7 parameters.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core purpose ('search requests') and key features ('query filters'). It wastes no words and is appropriately sized for the tool's complexity, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the tool's complexity (7 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain return values, error conditions, or behavioral traits like whether it's idempotent or safe. For a search tool with multiple filters and no structured output documentation, more context is needed to guide effective usage.

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%, so the schema fully documents all parameters. The description adds minimal value by listing filter types (method, content, headers, date range, type), which partially overlaps with schema details but doesn't provide additional semantics beyond what's already in the structured fields. This meets the baseline for high schema coverage.

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 verb ('search') and resource ('requests sent to a webhook'), specifying the action and target. It distinguishes from siblings like 'get_webhook_requests' by mentioning query filters, though not explicitly naming alternatives. However, it lacks explicit sibling differentiation, preventing a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'get_webhook_requests' or 'get_latest_request'. It mentions query filters but doesn't specify scenarios where filtering is needed or when other tools might be more appropriate, leaving the agent with insufficient context for optimal selection.

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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