Twitter Timeline Pay Per Result
Pay $0.30 for 1,000 posts
Twitter Timeline Pay Per Result
Pay $0.30 for 1,000 posts
Scrap Twitter timeline fast and easy. It is designed to be fast and efficient, so it can extract a large number of post for low price.
You can access the Twitter Timeline Pay Per Result programmatically from your own applications by using the Apify API. You can choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1# Start Server-Sent Events (SSE) session
2curl https://actors-mcp-server.apify.actor/sse?token=<APIFY_TOKEN>
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1faUsing Twitter Timeline Pay Per Result via Model Context Protocol (MCP) server
MCP server lets you use Twitter Timeline Pay Per Result within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Twitter Timeline Pay Per Result Actor with the provided input.
1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2 "jsonrpc": "2.0",
3 "id": 1,
4 "method": "tools/call",
5 "params": {
6 "arguments": { # Actor inputs
7 "username": ...,
8 "max_posts": ...,
9 ...
10 },
11 "name": "lw4wgsTf2pIShphkK"
12 }
13}'The response should be: Accepted. You should received response via SSE (JSON) as:
1event: message
2data: {
3 "result": {
4 "content": [{
5 "type": "text"
6 "text": "ACTOR_RESPONSE"
7 }]
8 }
9}Configure local MCP Server via standard input/output for Twitter Timeline Pay Per Result
You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:
1{
2"mcpServers": {
3 "actors-mcp-server": {
4 "command": "npx",
5 "args": [
6 "-y", "@apify/actors-mcp-server",
7 "--actors", "lw4wgsTf2pIShphkK"
8 ],
9 "env": {
10 "APIFY_TOKEN": "YOUR_API_TOKEN"
11 }
12 }
13}
14}You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.
To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.
Jan DaneckiActor Metrics
16 Monthly users
5.0 / 5 (1)
5 bookmarks
>99% runs succeeded
9.7 hours response time
Created in Mar 2024
Modified a month ago
