Twitter / X

Live

OAUTH 2.0

SOCIAL MEDIA

Media

Every tweet, mention, and DM your brand manages lives on Twitter / X. Twitter / X MCP gives your agent authenticated access to social data scoped to the user who authorized it.

  • Acts as the user: Access and write actions stay tied to the Twitter / X account that authorized the agent.
  • Credentials stay vaulted: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: Permissions enforced. 90-day audit trail.
Twitter / X
agent · Acme Q3
Run
Find all mentions of [brand] in the last 24 hours and summarize sentiment.
S
twitter_tweets_search
520ms
Social media agent
47 mentions in the last 24 hours. Sentiment: 62% positive, 28% neutral, 10% negative. Top positive: new feature launch praise. Top negative: 3 complaints about API rate limits. 2 influencer mentions with 50K+ followers.
Sources: Twitter search, last 24 hours
twitterxmcp
47 tweets
18:29
Message Claude...

Tools your social media agent reaches for on Twitter / X, scoped per user.

CALL ANY TOOL
Search tweets by keyword or hashtag, post from the authorized account, retrieve user profiles, and read the timeline.
twitter_tweets_search
Search tweets
Search recent tweets by keyword, hashtag, or user.
Parameters
Name
Type
Required
Description
query
string
Required
Search query: supports operators like from:, #, AND, OR
max_results
integer
Optional
Max results: 10-100
start_time
string
Optional
Start time: ISO 8601
twitter_tweet_get
Get tweet
twitter_tweet_create
Post tweet
twitter_user_get
Get user
twitter_timeline_get
Get timeline
Build your Agent
Drop the toolkit in, point it at the user, and your social media agent can use Twitter / X from the first run.
import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["twitterx"], toolNames: ["twitter_tweets_search", "twitter_tweet_get", "twitter_tweet_create"] },
pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
name: t.tool.definition.name,
description: t.tool.definition.description,
schema: z.object({}).passthrough(),
func: async (args) => {
const { data } = await sk.tools.executeTool({
toolName: t.tool.definition.name,
identifier: "user_123",
params: args,
});
return JSON.stringify(data);
},
}));

const agent = createReactAgent({ llm, tools: lcTools });
import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["twitterx"], toolNames: ["twitter_tweets_search", "twitter_tweet_get", "twitter_tweet_create"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
type: "function",
function: {
name: t.tool.definition.name,
description: t.tool.definition.description,
parameters: t.tool.definition.input_schema,
},
}));

const resp = await openai.responses.create({
model: "gpt-4o", input: prompt, tools: llmTools,
});
import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["twitterx"], toolNames: ["twitter_tweets_search", "twitter_tweet_get", "twitter_tweet_create"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
name: t.tool.definition.name,
description: t.tool.definition.description,
input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
model: "claude-sonnet-4-6", max_tokens: 1024,
tools: llmTools,
messages: [{ role: "user", content: prompt }],
});
import { Agent } from "@google/adk/agents";
import {
MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
connectionParams: new StreamableHTTPConnectionParams({
url: "https://mcp.scalekit.com/twitterx",
headers: { Authorization: `Bearer ${userScopedToken}` },
}),
});

const agent = new Agent({
name: "agent", model: "gemini-2.0-flash",
tools: await toolset.getTools(),
});
Try these prompts
Paste any prompt into your agent to start using Twitter / X.
Search & monitor
Copy the prompt
Copied
Find all mentions of [brand] in the last 24 hours.
Copy the prompt
Copied
Search for [hashtag] tweets today.
Copy the prompt
Copied
Find tweets from [username] this week.
Copy the prompt
Copied
Search for [competitor] mentions with negative sentiment.
Post & engage
Copy the prompt
Copied
Post a tweet: [text].
Copy the prompt
Copied
Reply to tweet [id]: [text].
Copy the prompt
Copied
Get my home timeline.
Copy the prompt
Copied
Get profile for @[username].
Analytics
Copy the prompt
Copied
Which of my tweets got the most engagement this week?
Copy the prompt
Copied
Get metrics for tweet [id].
Copy the prompt
Copied
Find influencer mentions of [brand] this month.
Copy the prompt
Copied
How many times was [hashtag] used today?
SEE HOW AUTH WORKS
Users authorize Twitter / X once. Their credentials stay vaulted, every call is checked, and every action is logged.
1
Authorize
Your user connects
Twitter / X
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
Twitter / X
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
Twitter / X
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
Twitter / X
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
Same per-user auth pattern across other social media agents and MCP connectors. Working code, live demos, fork what fits.
SALES
Outbound prospecting agent
Build targeted prospect lists with Apollo, enrich with firmographic data, and draft personalised outreach. Runs on a schedule.
GTM
HubSpot to Slack updates agent
Watch HubSpot deal stage changes and post structured updates to the right Slack channel. Reps stop checking the CRM all day.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
Other connector libraries treat auth as a demo afterthought. Scalekit starts with user identity, scope enforcement, and audit.
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.
// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Twitter / X today. Others tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions
Does the agent access Twitter / X as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.
Where is the Twitter / X oauth 2.0 stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.
Can I limit what the agent is allowed to do in Twitter / X?
Yes. Pass a tool name filter to listScopedTools so the social media agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Twitter / X.
What happens when a user revokes Twitter / X access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.
Does the agent post as the user or as a bot account?
As the authorizing user. All tweets post from that user's Twitter handle. The authorized user's account, API tier, and rate limits apply. Audit logs attribute each post to that user's connected account.
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""twitterx"": {
""url"": ""https://mcp.scalekit.com/twitterx"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.twitterx]
url = ""https://mcp.scalekit.com/twitterx""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""twitterx"": {
""url"": ""https://mcp.scalekit.com/twitterx"",
""type"": ""http""
}
}
}