LLM Context

Paid LLM Context proxy via x402 pay-per-use (HTTP 402).

Prerequisites: This skill requires x402-payment. Complete the setup steps before first use.

Service URLs

Role	Domain
API Provider	https://www.cpbox.io
Facilitator

https://www.cppay.finance |

Endpoint (Agent Interface)

CODEBLOCK0

Payment Flow (x402 Protocol)

1. 1. First request (no PAYMENT-SIGNATURE) -> 402 Payment Required with requirements JSON
2. Client signs (EIP-712) -> INLINECODE2
3. Retry with PAYMENT-SIGNATURE -> Server settles and returns JSON

With @springmint/x402-payment or x402-sdk-go, payment is automatic.

LLM Context delivers pre-extracted, relevance-ranked web content optimized for grounding LLM responses in real-time search results. Unlike traditional web search APIs that return links and snippets, LLM Context extracts the actual page content—text chunks, tables, code blocks, and structured data—so your LLM or AI agent can reason over it directly.

LLM Context vs AI Grounding

Feature	LLM Context (this)	AI Grounding (answers)
Output	Raw extracted content for YOUR LLM	End-to-end AI answers with citations
Interface

REST API (GET/POST) | OpenAI-compatible /chat/completions | | Searches | Single search per request | Multi-search (iterative research) | | Speed | Fast (<1s) | Slower | | Plan | Search | Answers | | Endpoint | /res/v1/llm/context | /res/v1/chat/completions | | Best for | AI agents, RAG pipelines, tool calls | Chat interfaces, research mode |

Endpoint

CODEBLOCK1

Authentication: handled by x402 payment middleware

Optional Headers:

• - Accept-Encoding: gzip — Enable gzip compression

Quick Start

GET Request

CODEBLOCK2

POST Request (JSON body)

CODEBLOCK3

With Goggles (Inline)

CODEBLOCK4

Using with x402-payment

CODEBLOCK5

Parameters

Query Parameters

Parameter	Type	Required	Default	Description
INLINECODE11	string	Yes	-	Search query (1-400 chars, max 50 words)
INLINECODE12

string | No | US | Search country (2-letter country code or ALL) | | search_lang | string | No | en | Language preference (2+ char language code) | | count | int | No | 20 | Max search results to consider (1-50) |

Context Size Parameters

Parameter	Type	Required	Default	Description
INLINECODE19	int	No	INLINECODE20	Max URLs in response (1-50)
INLINECODE21

int | No | 8192 | Approximate max tokens in context (1024-32768) | | maximum_number_of_snippets | int | No | 50 | Max snippets across all URLs (1-100) | | maximum_number_of_tokens_per_url | int | No | 4096 | Max tokens per individual URL (512-8192) | | maximum_number_of_snippets_per_url | int | No | 50 | Max snippets per individual URL (1-100) |

Filtering & Local Parameters

Parameter	Type	Required	Default	Description
INLINECODE29	string	No	INLINECODE30	Relevance threshold for including content (strict/balanced/lenient)
INLINECODE34

bool | No | null | Local recall control (true/false/null, see below) | | goggles | string/list | No | null | Goggle URL or inline definition for custom re-ranking |

Context Size Guidelines

Task Type	count	max_tokens	Example
Simple factual	5	2048	"What year was Python created?"
Standard queries

20 | 8192 | "Best practices for React hooks" | | Complex research | 50 | 16384 | "Compare AI frameworks for production" |

Larger context windows provide more information but increase latency and cost (of your inference). Start with defaults and adjust.

Threshold Modes

Mode	Behavior
INLINECODE41	Higher threshold — fewer but more relevant results
INLINECODE42

Default — good balance between coverage and relevance | | lenient | Lower threshold — more results, may include less relevant content |

Local Recall

The enable_local parameter controls location-aware recall:

Value	Behavior
INLINECODE45 (not set)	Auto-detect — local recall enabled when any location header is provided
INLINECODE46

Force local — always use local recall, even without location headers |
| false | Force standard — always use standard web ranking, even with location headers |

For most use cases, omit enable_local and let the API auto-detect from location headers.

Location Headers

Header	Type	Description
INLINECODE49	float	Latitude (-90.0 to 90.0)
INLINECODE50

float | Longitude (-180.0 to 180.0) | | X-Loc-City | string | City name | | X-Loc-State | string | State/region code (ISO 3166-2) | | X-Loc-State-Name | string | State/region name | | X-Loc-Country | string | 2-letter country code | | X-Loc-Postal-Code | string | Postal code |

Priority: X-Loc-Lat + X-Loc-Long take precedence. When provided, text-based headers (City, State, Country, Postal-Code) are not used for location resolution. Provide text-based headers only when you don't have coordinates.

Example: With Coordinates

CODEBLOCK6

Example: With Place Name

CODEBLOCK7

Goggles (Custom Ranking)

Goggles let you control which sources ground your LLM — essential for RAG quality.

Use Case	Goggle Rules
Official docs only	INLINECODE58
Exclude user content

$discard,site=reddit.com\n$discard,site=stackoverflow.com |
| Academic sources | $discard\n$site=arxiv.org\n$site=.edu |
| No paywalls | $discard,site=medium.com |

Method	Example
Hosted	INLINECODE62
Inline

--data-urlencode 'goggles=$discard\n$site=example.com' |

Hosted goggles should be hosted on a public URL and include ! name:, ! description:, ! author: headers. Inline rules need no registration.

Syntax: $boost=N / $downrank=N (1–10), $discard, $site=example.com. Combine with commas: $site=example.com,boost=3. Separate rules with \n (%0A).

Allow list: $discard\n$site=docs.python.org\n$site=developer.mozilla.org — Block list: INLINECODE75

Resources: See your upstream provider's Goggles documentation.

Response Format

Standard Response

CODEBLOCK8

Local Response (with enable_local)

CODEBLOCK9

Response Fields

Field	Type	Description
INLINECODE77	object	Container for all grounding content by type
INLINECODE78

array | Array of URL objects with extracted content (main grounding data) | | grounding.generic[].url | string | Source URL | | grounding.generic[].title | string | Page title | | grounding.generic[].snippets | array | Extracted smart chunks relevant to the query | | grounding.poi | object/null | Point of interest data (only with local recall) | | grounding.poi.name | string/null | Point of interest name | | grounding.poi.url | string/null | POI source URL | | grounding.poi.title | string/null | POI page title | | grounding.poi.snippets | array/null | POI text snippets | | grounding.map | array | Map/place results (only with local recall) | | grounding.map[].name | string/null | Place name | | grounding.map[].url | string/null | Place source URL | | grounding.map[].title | string/null | Place page title | | grounding.map[].snippets | array/null | Place text snippets | | sources | object | Metadata for all referenced URLs, keyed by URL | | sources[url].title | string | Page title | | sources[url].hostname | string | Source hostname | | sources[url].age | array/null | Page modification dates (when available) |

Note: Snippets may contain plain text OR JSON-serialized structured data (tables, schemas, code blocks). LLMs handle this mixed format well.

Use Cases

• - AI Agents: Give your agent a web search tool that returns ready-to-use content in a single call
• RAG Pipelines: Ground LLM responses in fresh, relevant web content
• AI Assistants & Chatbots: Provide factual answers backed by real sources
• Question Answering: Retrieve focused context for specific queries
• Fact Checking: Verify claims against current web content
• Content Research: Gather source material on any topic with one API call

Best Practices

• - Token budget: Start with defaults (maximum_number_of_tokens=8192, count=20). Reduce for simple lookups, increase for complex research.
• Source quality: Use Goggles to restrict to trusted sources. Set context_threshold_mode=strict when precision > recall.
• Performance: Use smallest count and maximum_number_of_tokens that meet your needs. For local queries, provide location headers.