xpoz-best-practices

Xpoz Best Practices

Overview

Xpoz is a social media intelligence platform providing access to Twitter/X, Instagram, Reddit, and TikTok data through MCP tools, Python SDK, TypeScript SDK, and CLI — no social media API keys required.

When to Use

Load this skill for any Xpoz interaction — not just when the user explicitly asks about best practices. It provides the context needed to use Xpoz tools correctly:

• Calling any Xpoz MCP tool (query syntax, field selection, response modes)
• Writing code with the Python or TypeScript SDK
• Using the Xpoz CLI
• Setting up authentication or tracking
• Troubleshooting errors or empty results
• Choosing which tool to use for a specific task

Quick Start

MCP — add the Xpoz MCP server to your agent's config. The server URL is https://mcp.xpoz.ai/mcp. Most MCP clients handle OAuth automatically on first tool call.

Example for Claude Code (~/.claude.json):

{
  "mcpServers": {
    "xpoz": {
      "url": "https://mcp.xpoz.ai/mcp",
      "transport": "streamable-http"
    }
  }
}

Python SDK:

pip install xpoz

from xpoz import XpozClient
client = XpozClient()  # reads XPOZ_API_KEY env var
results = client.twitter.search_posts("artificial intelligence")
print(f"Found {results.pagination.total_rows:,} tweets")
client.close()

TypeScript SDK:

npm install @xpoz/xpoz

import { XpozClient } from "@xpoz/xpoz";
const client = new XpozClient();
await client.connect();
const results = await client.twitter.searchPosts("artificial intelligence");
console.log(`Found ${results.pagination.totalRows.toLocaleString()} tweets`);
await client.close();

CLI:

pip install xpoz-cli
xpoz-cli twitter search_posts --query "artificial intelligence" --limit 20

See references/authentication.md for detailed auth flows (MCP, SDK, CLI). See references/sdk.md for complete Python & TypeScript SDK reference. See references/cli.md for CLI installation, commands, and rendering modes.

Query Syntax

All keyword search tools support boolean query syntax:

Operator	Example	Effect
Exact phrase	"machine learning"	Matches exact phrase
OR	"AI" OR "artificial intelligence"	Matches either term
AND	"Tesla" AND "earnings"	Matches both terms
Grouping	("deep learning" OR "neural network") AND python	Combines operators

Date filtering: Use startDate / endDate in YYYY-MM-DD format. Omit to use defaults (varies by tool).

Content filtering (Twitter only): Set filterOutRetweets: true to exclude retweets.

Forbidden in query string: from:, to:, lang:, since:, until:, filter: — use dedicated parameters instead.

Platform Quick Reference

Twitter/X (13 tools)

Tool	Purpose
getTwitterUser / getTwitterUsers	Look up 1-100 users by ID or username
searchTwitterUsers	Fuzzy search users by name
getTwitterUserConnections	Get followers or following
getTwitterUsersByKeywords	Find users who posted about a topic
getTwitterPostsByIds	Get 1-100 posts by ID
getTwitterPostsByAuthor	Get all posts from a username
getTwitterPostsByKeywords	Search posts by keywords
getTwitterPostRetweets	Get retweets of a post
getTwitterPostQuotes	Get quote tweets of a post
getTwitterPostComments	Get replies to a post
getTwitterPostInteractingUsers	Get commenters, quoters, or retweeters
countTweets	Count tweets matching a phrase

See references/twitter.md for all parameters, fields, and examples.

Instagram (9 tools)

Tool	Purpose
getInstagramUser	Look up user by ID or username
searchInstagramUsers	Fuzzy search users by name
getInstagramUserConnections	Get followers or following
getInstagramUsersByKeywords	Find users who posted about a topic
getInstagramPostInteractingUsers	Get commenters or likers of a post
getInstagramPostsByIds	Get posts by strong_id
getInstagramPostsByUser	Get posts from a user
getInstagramPostsByKeywords	Search posts by keywords in captions/subtitles
getInstagramCommentsByPostId	Get comments on a post

See references/instagram.md for all parameters, fields, and examples.

Reddit (9 tools)

Tool	Purpose
getRedditUser	Look up user by username
searchRedditUsers	Fuzzy search users by name
getRedditUsersByKeywords	Find users who posted about a topic
getRedditPostsByKeywords	Search posts by keywords
getRedditPostWithCommentsById	Get a post with all its comments
getRedditCommentsByKeywords	Search comments by keywords
searchRedditSubreddits	Search subreddits by name
getRedditSubredditWithPostsByName	Get subreddit details with posts
getRedditSubredditsByKeywords	Search subreddits by keyword in description

See references/reddit.md for all parameters, fields, and examples.

TikTok (9 tools)

Tool	Purpose
getTiktokUser	Look up user by ID or username
searchTiktokUsers	Fuzzy search users by name
getTiktokUsersByKeywords	Find users who posted about a topic
getTiktokUsersByHashtags	Find users who used specific hashtags
getTiktokPostsByIds	Get posts by ID
getTiktokPostsByUser	Get posts from a user
getTiktokPostsByKeywords	Search posts by keywords
getTiktokPostsByHashtags	Search posts by hashtags
getTiktokCommentsByPostId	Get comments on a post

See references/tiktok.md for all parameters, fields, and examples.

Tracking

Setting up tracking is a best practice for getting more complete data from Xpoz. Tracked items are crawled regularly in the background, which means:

• Better coverage — continuous collection captures posts and activity that a single point-in-time query might miss
• More complete data — tracked items accumulate data over time, giving you a fuller picture than one-off queries

Track keywords, users, subreddits, and hashtags across all 4 platforms.

Supported types per platform:

Platform	keyword	user	subreddit	hashtag
Twitter	Yes	Yes	—	—
Instagram	Yes	Yes	—	—
Reddit	Yes	Yes	Yes	—
TikTok	Yes	Yes	—	Yes

View current tracking:

MCP:        call getTrackedItems
Python:     client.tracking.get_tracked_items()
TypeScript: await client.tracking.getTrackedItems()
CLI:        xpoz-cli tracking get_tracked_items

Add tracked items:

MCP:        call addTrackedItems with items: [{ phrase: "AI agents", type: "keyword", platform: "twitter" }]
Python:     client.tracking.add_tracked_items([{ "phrase": "AI agents", "type": "keyword", "platform": "twitter" }])
TypeScript: await client.tracking.addTrackedItems([{ phrase: "AI agents", type: "keyword", platform: "twitter" }])
CLI:        xpoz-cli tracking add_tracked_items --items '[{"phrase": "AI agents", "type": "keyword", "platform": "twitter"}]'

Remove tracked items:

MCP:        call removeTrackedItems with items: [{ phrase: "AI agents", type: "keyword", platform: "twitter" }]
Python:     client.tracking.remove_tracked_items([...])
TypeScript: await client.tracking.removeTrackedItems([...])
CLI:        xpoz-cli tracking remove_tracked_items --items '[{"phrase": "AI agents", "type": "keyword", "platform": "twitter"}]'

See xpoz-social-tracking for full tracking workflows and advanced patterns.

Response Modes

All paginated tools support three response modes via responseType:

Mode	Behavior	Best For
"fast" (default)	Returns up to 300 results immediately	Quick lookups, exploration
"paging"	Async — returns operationId, poll with checkOperationStatus	Large datasets, page-by-page
"csv"	Async CSV export to S3 — returns download URL	Bulk export, offline analysis

See references/pagination-and-export.md for async polling patterns, pagination, and CSV export details.

Field Selection

Pass fields to request only the data you need. This reduces response size and improves performance.

MCP:        fields: ["id", "text", "authorUsername", "likeCount"]
Python:     fields=["id", "text", "author_username", "like_count"]
TypeScript: fields: ["id", "text", "authorUsername", "likeCount"]
CLI:        --fields id text author_username like_count

Each platform has different available fields — see the platform-specific references for complete field lists.

Common Patterns

Search → Analyze → Export:

1. Search posts by keywords (fast mode) to preview results
2. Analyze engagement, sentiment, or themes
3. Export full dataset to CSV for deeper analysis

Find Users → Get Their Posts → Analyze:

1. Search users by keywords to find relevant accounts
2. Get posts by author for top accounts
3. Analyze content patterns, posting frequency, engagement

Data Freshness:

• Data is cached in Xpoz's database with automatic API fallback when stale — results are kept fresh automatically
• Use forceLatest: true to bypass cache and force a live fetch (increases latency and cost)

Troubleshooting

Problem	Solution
MCP: "Unauthorized"	Re-run OAuth flow — see references/authentication.md
SDK: AuthenticationError	Verify key at xpoz.ai/settings
Empty results	Check query syntax, widen date range, try different keywords
Stale data	Use forceLatest: true to bypass cache
Operation timeout	Keep polling checkOperationStatus every ~5s until status is no longer running
Token exchange fails	Ask user to re-authorize — codes are single-use

Detailed Guides

For complete parameters, response fields, patterns, and examples:

• references/authentication.md — Auth flows for MCP, SDK (API key), CLI
• references/sdk.md — Python & TypeScript SDK: setup, namespaces, pagination helpers, async patterns
• references/cli.md — CLI installation, command structure, rendering modes, examples
• references/pagination-and-export.md — Response modes, operationId polling, CSV export, field selection
• references/twitter.md — All 13 Twitter tools with parameters, fields, and examples
• references/instagram.md — All 9 Instagram tools with parameters, fields, and examples
• references/reddit.md — All 9 Reddit tools with parameters, fields, and examples
• references/tiktok.md — All 9 TikTok tools with parameters, fields, and examples

Example Prompts

• "How do I search for tweets about AI?"
• "What fields are available for Instagram posts?"
• "How do I export Reddit data to CSV?"
• "Set up tracking for my brand across all platforms"
• "How do I paginate through large result sets?"
• "What's the difference between fast mode and paging mode?"
• "How do I authenticate with the Xpoz Python SDK?"
• "Show me all available TikTok tools"