MCP for AI Clients
Connect Twitter/X data to Grok, Cursor, Claude Code, Codex, and your AI agents
Once TwtAPI MCP is configured, your AI client can search posts, inspect users, track trends, and keep moving through monitoring or research work without breaking context.
Example prompts
These are good first requests to test after setup.
Prompt
Analyze what @solana has been talking about in the last 30 tweets
Prompt
Find the most relevant posts mentioning "ai agent" in the last 24 hours
Prompt
List high-engagement followers of @openai and group them by profile type
Why MCP
Why turn an API into an MCP tool
MCP does not replace the API. It brings TwtAPI into the AI tools you already use so research and analysis can happen there directly.
Less glue code
Many tasks that used to require reading docs, assembling endpoints, and parsing payloads can now happen directly in the client.
Context stays in the conversation
You can keep comparing accounts, refining searches, and extending analysis without dropping back into separate scripts or tabs.
Better fit for analysis work
Competitor research, account profiling, trend discovery, and audience exploration feel much more natural through MCP.
Built on the same TwtAPI backend
You still rely on the same TwtAPI capabilities and permissions. You only need to generate an MCP key in your dashboard.
Use Cases
Where MCP fits best
If you spend more time working inside an AI client than building a custom integration layer, MCP is often the faster path.
Account research
Ask AI to summarize recent themes, high-engagement posts, and activity patterns for any target account.
Trend search
Search by keyword, topic, or advanced query syntax and let AI organize notable posts, accounts, and narratives.
Agent workflows
Expose TwtAPI to Grok, Cursor, Claude Code, Codex, or any MCP-compatible client so your AI can fetch data, structure it, and continue the workflow automatically.
What You Can Do
Use MCP to run common Twitter/X data tasks directly inside your AI client
Most users do not care about the protocol itself. They care about whether setup leads quickly to useful work: searching posts, checking accounts, monitoring topics, and handing results back to AI for analysis.
Search and analyze in the same conversation
You do not need to bounce between a client, API docs, and raw payloads. Once data is returned, you can keep summarizing, filtering, and comparing inside the same thread.
Bring search, account lookup, and monitoring into daily workflows
Typical uses include keyword search, account research, competitor tracking, trend review, and routing results into reports, notes, or internal workflows.
Start with one real request before expanding
Many teams begin with one or two real questions, check the output quality, and only then expand into broader monitoring or automation.
Quickstart
Set it up in 3 steps
Generate your key, copy the matching snippet, restart the client, and start testing.
1. Generate your MCP key
Sign in to the dashboard and create or reset the `sk-` MCP key in API Settings.
2. Copy the matching client config
Choose the server URL, JSON config, or CLI command that matches your client.
3. Restart the client and start using tools
After restarting the MCP service, TwtAPI tools become available inside the conversation.
Next Step
Pick the page that matches the job you want to run
Once MCP is connected, the easiest next move is to open the page that matches your current task and continue from there.
Twitter/X API MCP Server
Start here if you still need to compare official X MCP, TwtAPI MCP, direct API calls, and scraper-based tools.
Continue
Twitter/X API for AI Agents
Best when your agent needs to search posts, inspect users, and keep Twitter/X context inside the task.
Continue
Twitter Monitoring API
Best when the workflow is really about keywords, watchlists, alerts, brand monitoring, or competitor tracking.
Continue
Twitter/X API Pricing
Use this before a recurring agent or monitoring workflow starts running every day.
Continue
API Docs
Go here when you already know which endpoint, parameter, or response shape the client should use.
Continue
Client Setup
Supported clients and setup methods
Use these snippets as starting templates. Replace `sk-your-mcp-key` with your real MCP key before connecting.
Cursor
Ideal for editor-based workflows where AI and code live side by side.
Config file path: ~/.cursor/mcp.json
Write or merge this JSON into `mcp.json`, then restart Cursor MCP servers.
{
"mcpServers": {
"twtapi": {
"url": "https://mcp.twtapi.com/sse?mcp_key=sk-your-mcp-key"
}
}
}Claude Code
Quick SSE setup for command-line oriented workflows.
Run this once to add the twtapi server and start using it from Claude Code.
claude mcp add --transport sse twtapi "https://mcp.twtapi.com/sse?mcp_key=sk-your-mcp-key"
Codex CLI
Codex connects over Streamable HTTP with a bearer token env var.
Export the env var first, then add the server so Codex can connect via `/mcp`.
export TWTAPI_MCP_KEY="sk-your-mcp-key" codex mcp add twtapi --url "https://mcp.twtapi.com/mcp" --bearer-token-env-var TWTAPI_MCP_KEY
Grok
Use Grok Custom Connectors to call live Twitter/X data through TwtAPI.
Open grok.com/connectors, choose New Connector -> Custom, then paste the TwtAPI SSE server URL below.
Name: TwtAPI Server URL: https://mcp.twtapi.com/sse?mcp_key=sk-your-mcp-key Open grok.com/connectors, choose New Connector -> Custom, then paste the server URL.
Other MCP clients
Use this for MCP-compatible clients and agent runners that accept a remote SSE server.
If your client asks for a server URL, start with this SSE endpoint.
https://mcp.twtapi.com/sse?mcp_key=sk-your-mcp-key
FAQ
Common questions
Does MCP replace the API docs?
No. The API docs remain the right choice for direct application integration. MCP is for AI clients that should call TwtAPI inside natural-language workflows.
Do I need to deploy my own MCP server?
No. You only need an existing account and an MCP key generated from the dashboard. We already host the MCP endpoints.
Can I use TwtAPI MCP with Grok or other MCP-compatible clients?
Yes. Grok Custom Connectors can use the TwtAPI SSE URL. Cursor, Claude Code, and many general MCP clients also work with SSE, while Codex CLI is best connected over Streamable HTTP.
Which protocols are supported?
TwtAPI MCP supports SSE and Streamable HTTP. Grok, Cursor, Claude Code, and most general MCP clients use SSE; Codex CLI uses Streamable HTTP.
Bring TwtAPI MCP into your AI workflow
If you already have an account, generate your MCP key and connect a client. If you are still evaluating, start with the API docs and AI workflow pages so you can compare the setup path with your use case.