llm-context

by brave

USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity.… npx skills add https://github.com/brave/brave-search-skills --skill llm-context Download ZIPGitHub158

LLM Context

Requires API Key: Get one at https://api.search.brave.com

Plan: Included in the Search plan. See https://api-dashboard.search.brave.com/app/subscriptions/subscribe

Brave LLM Context API 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

GET https://api.search.brave.com/res/v1/llm/context
POST https://api.search.brave.com/res/v1/llm/context

Authentication: X-Subscription-Token: <API_KEY> header

Optional Headers:

• Accept-Encoding: gzip — Enable gzip compression

Parameters

Query Parameters

Parameter Type Required Default Description q string Yes - Search query (1-400 chars, max 50 words) country 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 maximum_number_of_urls int No 20 Max URLs in response (1-50) maximum_number_of_tokens 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 context_threshold_mode string No balanced Relevance threshold for including content (strict/balanced/lenient) enable_local 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 strict Higher threshold — fewer but more relevant results balanced 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 null (not set) Auto-detect — local recall enabled when any location header is provided true 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 X-Loc-Lat float Latitude (-90.0 to 90.0) X-Loc-Long 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

curl -s "https://api.search.brave.com/res/v1/llm/context" \
 -H "Accept: application/json" \
 -H "X-Subscription-Token: ${BRAVE_SEARCH_API_KEY}" \
 -H "X-Loc-Lat: 37.7749" \
 -H "X-Loc-Long: -122.4194" \
 -G \
 --data-urlencode "q=best coffee shops near me"

Example: With Place Name

curl -s "https://api.search.brave.com/res/v1/llm/context" \
 -H "Accept: application/json" \
 -H "X-Subscription-Token: ${BRAVE_SEARCH_API_KEY}" \
 -H "X-Loc-City: San Francisco" \
 -H "X-Loc-State: CA" \
 -H "X-Loc-Country: US" \
 -G \
 --data-urlencode "q=best coffee shops near me"

Goggles (Custom Ranking) — Unique to Brave

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

Use Case Goggle Rules Official docs only $discard\n$site=docs.python.org 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 --data-urlencode "goggles=https://raw.githubusercontent.com/brave/goggles-quickstart/main/goggles/1k_short.goggle" Inline --data-urlencode 'goggles=$discard\n$site=example.com'

Hosted goggles must be on GitHub/GitLab, include ! name:, ! description:, ! author: headers, and be registered at https://search.brave.com/goggles/create. 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: $discard,site=pinterest.com\n$discard,site=quora.com

Resources: Discover · Syntax · Quickstart

Response Format

Standard Response

{
 "grounding": {
 "generic": [
 {
 "url": "https://example.com/page",
 "title": "Page Title",
 "snippets": [
 "Relevant text chunk extracted from the page...",
 "Another relevant passage from the same page..."
 ]
 }
 ],
 "map": []
 },
 "sources": {
 "https://example.com/page": {
 "title": "Page Title",
 "hostname": "example.com",
 "age": ["Wednesday, January 15, 2025", "2025-01-15", "392 days ago"]
 }
 }
}

Local Response (with enable_local)

{
 "grounding": {
 "generic": [...],
 "poi": {
 "name": "Business Name",
 "url": "https://business.com",
 "title": "Title of business.com website",
 "snippets": ["Business details and information..."]
 },
 "map": [
 {
 "name": "Place Name",
 "url": "https://place.com",
 "title": "Title of place.com website",
 "snippets": ["Place information and details..."]
 }
 ]
 },
 "sources": {
 "https://business.com": {
 "title": "Business Name",
 "hostname": "business.com",
 "age": null
 }
 }
}

Response Fields

Field Type Description grounding object Container for all grounding content by type grounding.generic 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.