SearchPipe

searchpipe_search

Run an AI-powered web search for a query: multi-engine retrieval → page fetching → LLM reranking → optional AI answer.

Uses the same commercial pipeline as the HTTP POST /search endpoint: authentication → rate limiting → input moderation → credit charge → search → output moderation + AI-generated marker → refund on failure → usage logging. Credits are charged per call.

api_key: an API key starting with sp-. It may also be provided through the SEARCHPIPE_API_KEY environment variable (the parameter takes precedence). Returns Tavily-style structured results (query / answer / results[]). Returns a tool error on authentication failure, insufficient credits, content violation, or retrieval failure.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes
`api_key`	No
`max_results`	No
`include_answer`	No
`include_raw_content`	No

Output Schema

TableJSON Schema

Name	Required	Description
`query`	Yes
`answer`	No	LLM-generated answer (optional)
`results`	Yes
`ai_generated`	No	Whether the response contains LLM-generated content

Schema Changelog

Changes observed during successful MCP inspections.

Changed11 schema fields changedSep 15, 2026
- addedOutput schema / properties / ai_generated / title
```
Added value: +"Ai Generated"
```
- addedOutput schema / properties / answer / title
```
Added value: +"Answer"
```
- addedOutput schema / properties / query / title
```
Added value: +"Query"
```
- addedOutput schema / properties / results / items / properties / content / title
```
Added value: +"Content"
```
- addedOutput schema / properties / results / items / properties / raw_content / title
```
Added value: +"Raw Content"
```
- addedOutput schema / properties / results / items / properties / score / title
```
Added value: +"Score"
```
- addedOutput schema / properties / results / items / properties / title / title
```
Added value: +"Title"
```
- addedOutput schema / properties / results / items / properties / url / title
```
Added value: +"Url"
```
- addedOutput schema / properties / results / items / title
```
Added value: +"SearchResult"
```
- addedOutput schema / properties / results / title
```
Added value: +"Results"
```
- addedOutput schema / title
```
Added value: +"SearchResponse"
```
AddedSep 14, 2026

TDQS

A3.9/5.0

Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so thoroughly: it discloses the commercial pipeline, authentication, rate limiting, moderation, credit charging, refund on failure, usage logging, and specific tool error conditions. This is rich operational transparency.

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 front-loaded with the core purpose and then layers in necessary behavioral details. It is somewhat long but remains information-dense, with only minor repetition between the initial pipeline summary and the commercial pipeline breakdown.

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?

The tool has no annotations and low schema description coverage, so the description must compensate. It does an excellent job on behavior, errors, and authentication, but it leaves several input parameters unexplained, making it only partially complete for safe invocation.

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 description coverage is 0% and the description only documents api_key semantics (prefix, environment variable, precedence). It does not explain max_results, include_answer, or include_raw_content, leaving most parameters without semantic guidance.

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 states a specific verb and resource: 'Run an AI-powered web search for a query.' It clearly describes the tool's function and even outlines the internal pipeline, leaving no ambiguity about what it does.

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

Usage Guidelines3/5

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

Usage is implied by the name and the mention of an AI-powered web search, but the description does not explicitly state when to choose this tool over alternatives or when not to use it. It provides pipeline context rather than decision guidance.

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

All SearchPipe tools Inspect

Try in Browser

Give agents eyes on the webHosted screenshot MCP. Send a URL, get a pixel-perfect image. $0.002 per grab. Works with Claude, Cursor, and Codex.grabbit.liveAd

Glama MCP Gateway

Add one secure layer between your agents and this server.