TwitterAPI.io Docs▌
by dorukardahan
Offline access to TwitterAPI.io Docs — fuzzy search across 54 endpoints, step‑by‑step guides and clear pricing for quick
Offline access to TwitterAPI.io API documentation with fuzzy search across 54 endpoints, guides, and pricing details
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers building Twitter integrations
- / Learning TwitterAPI.io without internet access
- / Quick reference while coding Twitter bots
- / Understanding API costs and limits
capabilities
- / Search across 54 API endpoints with fuzzy search
- / Browse complete endpoint documentation with parameters and examples
- / Access authentication guides and code examples
- / Get pricing information and credit calculations
- / Retrieve guides on rate limits, webhooks, and streaming
- / Access blog posts with tutorials and use cases
what it does
Provides offline access to complete TwitterAPI.io documentation including 59 endpoints, guides, and examples. No API key required - everything is bundled locally.
about
TwitterAPI.io Docs is a community-built MCP server published by dorukardahan that provides AI assistants with tools and capabilities via the Model Context Protocol. Offline access to TwitterAPI.io Docs — fuzzy search across 54 endpoints, step‑by‑step guides and clear pricing for quick It is categorized under developer tools. This server exposes 7 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install TwitterAPI.io Docs in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
TwitterAPI.io Docs is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
twitterapi-io-mcp
Offline TwitterAPI.io documentation for Claude and AI assistants via MCP. 59 endpoints (with full method/params/body), 32 guides, 24 blog posts. No API key needed.
# Quick install (Claude Code)
claude mcp add twitterapi-io -- npx -y twitterapi-io-mcp
What is this?
An MCP server that gives Claude, Cursor, VS Code Copilot, and other AI assistants instant, offline access to TwitterAPI.io documentation.
- 59 API endpoints with full HTTP method, body/query parameters, cURL examples, and response schemas
- 32 guide pages covering pricing, authentication, rate limits, webhooks, streaming
- 24 blog posts with tutorials and use cases
- All v2 write endpoints documented with
login_cookies,proxy, and body params - 4 deprecated v1 endpoints marked with migration notices
- Zero API key required — everything is bundled locally
Unlike other Twitter MCP servers that proxy live API calls (and need your API key), this one ships a complete documentation snapshot. Your AI assistant reads it locally, instantly.
v1.0.23 Highlights
- Platform advisory: Twitter disabled
since:/until:search operators and pagination (~Mar 5, 2026). Workarounds documented indocs/platform-advisory-2026-03.md. - Workaround: Use
since_time:UNIX/until_time:UNIXformat instead (tested, working) - Webhook URL warning: URL not auto-restored after API key rotation — must be manually re-set
v1.0.22 Highlights
-
7 new endpoints (52 → 59 total):
get_space_detail,get_tweet_replies_v2,get_user_about,get_user_to_monitor_tweet,update_avatar_v2,update_banner_v2,update_profile_v2 -
Fresh rescrape from docs.twitterapi.io (Feb 21, 2026)
-
All 59 endpoints now match official llms.txt index
-
Scraper auto-extracts method/body/params —
npm run scrapekeeps data fresh
Disclaimer: Independent community project. Not affiliated with TwitterAPI.io.
Installation
Previously published as
twitterapi-docs-mcp? Just change the package name — everything else stays the same.
Requires: Node.js 18.18.0+
Claude Code (recommended)
# Add globally (all projects)
claude mcp add --scope user twitterapi-io -- npx -y twitterapi-io-mcp
# Or project-only
claude mcp add twitterapi-io -- npx -y twitterapi-io-mcp
# Verify
claude mcp list
Claude Desktop
Add to your config file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"twitterapi-io": {
"command": "npx",
"args": ["-y", "twitterapi-io-mcp"]
}
}
}
Cursor
Add to .cursor/mcp.json in your project root:
{
"mcpServers": {
"twitterapi-io": {
"command": "npx",
"args": ["-y", "twitterapi-io-mcp"]
}
}
}
VS Code / VS Code Insiders
Add to .vscode/mcp.json in your project root:
{
"servers": {
"twitterapi-io": {
"command": "npx",
"args": ["-y", "twitterapi-io-mcp"]
}
}
}
Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"twitterapi-io": {
"command": "npx",
"args": ["-y", "twitterapi-io-mcp"]
}
}
}
Docker
docker run -i --rm $(docker build -q .) 2>/dev/null
Or build from source:
git clone https://github.com/dorukardahan/twitterapi-io-mcp.git
cd twitterapi-io-mcp && npm install
node index.js
Available tools
| Tool | Description | Best for |
|---|---|---|
search_twitterapi_docs | Full-text search across all docs (fuzzy matching, typo-tolerant) | Finding endpoints, guides, or blog posts by keyword |
get_twitterapi_endpoint | Get full endpoint documentation with params, examples, response schema | Deep dive into a specific API endpoint |
list_twitterapi_endpoints | List endpoints, optionally filtered by category | Browsing what's available in a category |
get_twitterapi_guide | Get guide pages (pricing, auth, rate limits, webhooks, etc.) | Understanding platform rules and setup |
get_twitterapi_url | Fetch content by URL path or page key | When you have a direct link to docs |
get_twitterapi_pricing | Quick pricing overview | Cost questions |
get_twitterapi_auth | Quick authentication guide | Auth setup and API key usage |
For AI assistants
If you're an AI assistant using this MCP server, here's a quick reference:
| User wants... | Use this tool | Example |
|---|---|---|
| Find an endpoint | search_twitterapi_docs | query: "advanced search" |
| Endpoint details | get_twitterapi_endpoint | endpoint_name: "tweet_advanced_search" |
| List all endpoints | list_twitterapi_endpoints | category: "user" (optional) |
| Pricing info | get_twitterapi_pricing | No params needed |
| Auth guide | get_twitterapi_auth | No params needed |
| Any guide/page | get_twitterapi_guide | guide_name: "qps_limits" |
| Fetch by URL | get_twitterapi_url | url: "pricing" |
Tips:
- Search is fuzzy and typo-tolerant:
"twet object"still finds results - Use
max_results: 5for focused results - Check the
deprecation_noticefield — some legacy endpoints have v2 replacements
What can you ask?
Here are real prompts that work well with this MCP server:
- "What are the rate limits for TwitterAPI.io?" — triggers
get_twitterapi_guide - "Show me the tweet advanced search endpoint" — triggers
get_twitterapi_endpoint - "How do I authenticate with the API?" — triggers
get_twitterapi_auth - "What's the pricing?" — triggers
get_twitterapi_pricing - "List all user-related endpoints" — triggers
list_twitterapi_endpointswithcategory: "user" - "How do webhook filter rules work?" — triggers
search_twitterapi_docs - "What endpoints are deprecated?" — triggers
search_twitterapi_docswithquery: "deprecated" - "How do I upload media and create a tweet?" — triggers sequential
get_twitterapi_endpointcalls
| Category | Count | Endpoints |
|---|---|---|
| User | 12 | get_user_by_username, get_user_followers, get_user_followings, batch_get_user_by_userids, and 8 more |
| Tweet | 8 | tweet_advanced_search, get_tweet_by_ids, get_tweet_replies_v2, get_user_tweets, and 4 more |
| Community | 9 | create_community_v2, get_community_by_id, join_community_v2, and 6 more |
| Profile | 3 | update_avatar_v2, update_banner_v2, update_profile_v2 |
| Webhook | 4 | add_webhook_rule, get_webhook_rules, update_webhook_rule, delete_webhook_rule |
| Stream | 3 | add_user_to_monitor_tweet, get_user_to_monitor_tweet, remove_user_from_monitor_tweet |
| Action | 14 | create_tweet_v2, like_tweet_v2, retweet_tweet_v2, upload_media_v2, and 10 more |
| DM | 2 | send_dm_v2, get_dm_history_by_user_id |
| List | 2 | get_list_followers, get_list_members |
| Other | 2 | get_trends, get_space_detail |
Configuration
| Environment Variable | Default | Description |
|---|---|---|
TWITTERAPI_MCP_DISK_CACHE | 1 (on) | Set to 0 to disable disk caching |
Troubleshooting
npx hangs or fails on first run
The first run downloads the package from npm. If it hangs, try:
npx -y twitterapi-io-mcp@latest
Or install globally: npm install -g twitterapi-io-mcp
"Node.js version not supported"
This server requires Node.js 18.18.0 or later. Check your version:
node --version
claude mcp add not recognized
Make sure Claude Code CLI is installed and up to date:
claude --version
Server starts but no tools appear
Restart your MCP client after adding the server config. Most clients (Claude Desktop, Cursor) need a restart to detect new MCP servers.
How it works
┌─────────────┐ MCP (stdio) ┌──────────────────┐
│ Claude / │ ◄──────────────────► │ twitterapi-io-mcp│
│ Cursor / │ │ │
│ VS Code │ │ Bundled docs │
└─────────────┘ │ (59 endpoints) │
└──────────────────┘
No network needed
| Property | Value |
|---|---|
| Runtime | Node.js 18.18.0+ (ES Modules, no build step) |
| Protocol | MCP via stdio |
| Caching | Hybrid (memory + disk), 24h TTL |
| Search | N-gram tokenization with fuzzy matching |
- AI assistant calls an MCP tool (search, get endpoint, etc.)
- Server searches the bundled documentation snapshot
- Results return instantly with no network requests
Why I built this
I use TwitterAPI.io daily for my projects. Switching between my editor and their docs site got old fast. So I packaged the entire documentation into an MCP server. Now I ask Claude and get answers without leaving my terminal.
If you work with the Twitter/X API through TwitterAPI.io, this saves you the same context-switching. Install it, forget about it, and just ask.
Develo
FAQ
- What is the TwitterAPI.io Docs MCP server?
- TwitterAPI.io Docs is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for TwitterAPI.io Docs?
- This profile displays 58 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.8★★★★★58 reviews- ★★★★★Dhruvi Jain· Dec 28, 2024
TwitterAPI.io Docs has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Fatima Rahman· Dec 16, 2024
TwitterAPI.io Docs is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Anika Robinson· Dec 16, 2024
Useful MCP listing: TwitterAPI.io Docs is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Mei Sanchez· Dec 12, 2024
We wired TwitterAPI.io Docs into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Olivia Bhatia· Dec 8, 2024
TwitterAPI.io Docs is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Oshnikdeep· Nov 19, 2024
According to our notes, TwitterAPI.io Docs benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Emma Flores· Nov 7, 2024
I recommend TwitterAPI.io Docs for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Mei Ramirez· Nov 7, 2024
TwitterAPI.io Docs reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Li Thompson· Nov 3, 2024
We evaluated TwitterAPI.io Docs against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Camila Abbas· Oct 26, 2024
TwitterAPI.io Docs reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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