How do I use X Search MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@X Search MCP search for AI news from @OpenAI and @GoogleAI in the last week" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

X Search MCP

by konarkm

Overview Schema Related Servers Score Discussions

JavaScript

Remote

x-search-mcp

Minimal MCP server for xAI X search using the Responses API and structured outputs.

Features

Single MCP tool: x_search
Uses xAI Responses API with x_search tool calling
Structured output parsing + citation normalization

Related MCP server: x-mcp-server

Requirements

Node.js >= 18
XAI_API_KEY environment variable

MCP client config

Add the following config to your MCP client:

{
  "mcpServers": {
    "x-search": {
      "command": "npx",
      "args": ["-y", "x-search-mcp"],
      "env": {
        "XAI_API_KEY": "your-key-here"
      }
    }
  }
}

Local development

npm install
npm run build

Smoke test (optional)

XAI_API_KEY=your-key-here npm run build
XAI_API_KEY=your-key-here npm run smoke-test

Note: this test requires network access and may fail in restricted environments.

MCP Tool

`x_search`

Searches X with optional filters.

Input

{
  "query": "string",
  "allowed_x_handles": ["string"],
  "excluded_x_handles": ["string"],
  "from_date": "YYYY-MM-DD",
  "to_date": "YYYY-MM-DD",
  "enable_image_understanding": true,
  "enable_video_understanding": true,
  "include_raw_response": false
}

Output

{
  "answer": "string",
  "citations": ["https://x.com/..."],
  "inline_citations": [
    {
      "url": "https://x.com/...",
      "start_index": 10,
      "end_index": 42,
      "title": "1"
    }
  ],
  "raw_response": {}
}

Environment Variables

XAI_API_KEY (required)
XAI_MODEL (default: grok-4-1-fast)
XAI_BASE_URL (default: https://api.x.ai/v1)
XAI_TIMEOUT (default: 30000)

Notes

allowed_x_handles and excluded_x_handles are mutually exclusive.
Date filters must be YYYY-MM-DD and from_date must be <= to_date.
Tool responses are returned as MCP structuredContent (with a text fallback for display).
Citations are normalized from xAI response annotations when available.

Available Tools

1 tool

x_searchX SearchB

Read-only

Search X posts using xAI's Responses API x_search tool. Returns a normalized answer and citations.

ParametersJSON Schema

Name	Required	Description
`query`	Yes	Search query for X
`allowed_x_handles`	No	Only include posts from these handles
`excluded_x_handles`	No	Exclude posts from these handles
`from_date`	No	Start date (YYYY-MM-DD)
`to_date`	No	End date (YYYY-MM-DD)
`enable_image_understanding`	No	Enable image understanding
`enable_video_understanding`	No	Enable video understanding
`include_raw_response`	No	Include raw xAI response for debugging

Output Schema

ParametersJSON Schema

Name	Required	Description
`answer`	Yes
`citations`	Yes
`raw_response`	No
`inline_citations`	Yes

TDQS

B3.2/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=false. The description adds that it 'Returns a normalized answer and citations,' which provides useful context about the output format. However, it doesn't disclose other behavioral traits like rate limits, authentication needs, or what 'normalized' entails beyond what annotations cover.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences that directly state the tool's function and output. It's front-loaded with the main purpose. However, it could be slightly more structured by explicitly separating purpose from output details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 parameters, search functionality), annotations cover safety and scope, and an output schema exists, the description is reasonably complete. It mentions the API source and output format, but lacks usage context or behavioral details like error handling, which holds it back from a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all 8 parameters. The description doesn't add any parameter-specific information beyond what's in the schema. According to guidelines, with high schema coverage (>80%), the baseline is 3 even without param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Search X posts using xAI's Responses API x_search tool.' It specifies the action (search) and resource (X posts), and mentions the API source. However, with no sibling tools, it doesn't need to differentiate from alternatives, so it can't achieve a 5 for that criterion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, constraints, or scenarios where this tool is preferred. The only context is the API name, which doesn't help with usage decisions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

1 tool updatev1.0.0Jan 7, 2026
- First observedx_search

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

B3.3/5.0

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined as searching X posts using a specific API, making it unambiguous in isolation.

Naming Consistency5/5

Since there is only one tool, naming consistency is inherently perfect. The tool name 'x_search' follows a clear verb_noun pattern, and there are no other tools to create inconsistency.

Tool Count2/5

A single tool is too few for a server named 'X Search MCP', which implies a search-focused domain. This minimal set lacks basic operations like filtering, sorting, or handling search history, making it feel incomplete and under-scoped.

Completeness2/5

The server's domain appears to be searching X posts, but with only one search tool, there are significant gaps. Missing functionalities might include advanced search options, result pagination, or related operations like trending topics, making the surface severely incomplete for practical use.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

Need Help?

Reddit Discussion

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Looking for Admin?

If you are the server author, to access and configure the admin panel.

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x-search-mcp

Features

Requirements

MCP client config

Local development

Smoke test (optional)

MCP Tool

x_search

Environment Variables

Notes

Available Tools

Output Schema

TDQS

Tool Schema Changelog

TDQS

Maintenance

Resources

Looking for Admin?

Related MCP Connectors

Related MCP Servers

grok-mcp-server

x-mcp-server

x-search-mcp

grok-mcp

Latest Blog Posts

MCP directory API

`x_search`