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lluisfont

x-mcp-server

by lluisfont

X MCP Server

TypeScript Model Context Protocol (MCP) server for the official X API.

This project lets MCP-compatible agents, including ChatGPT agents, safely read from and publish to X accounts through a local server that runs on your own computer.

The server supports:

  • Reading the authenticated X account.

  • Looking up X users by username.

  • Reading posts by ID.

  • Listing recent posts from a user.

  • Searching recent posts with X search syntax.

  • Creating posts and replies when write mode is explicitly enabled.

  • Selecting a different X account per local computer installation.

  • Running over stdio for local MCP hosts.

  • Running over local Streamable HTTP for ChatGPT through OpenAI Secure MCP Tunnels.

Project Status

This is a functional MVP.

Implemented:

  • MCP server over stdio.

  • MCP server over Streamable HTTP.

  • Official X API client.

  • Local multi-account configuration.

  • Recommended xurl authentication provider, using X's official CLI for OAuth token storage, refresh and rotation.

  • Safe read-only mode by default.

  • Explicit read-write mode for publishing and replies.

  • Legacy local OAuth 2.0 Authorization Code + PKCE helper for direct env-token setups.

  • Unit tests with Vitest.

  • ChatGPT connection guide through OpenAI Secure MCP Tunnels.

  • Local server lifecycle guide for manual and automatic startup on Windows.

Related MCP server: X API FastMCP Server

How It Works

For local MCP hosts:

MCP host
  -> stdio
  -> x-mcp-server
  -> official X API

For ChatGPT agents:

ChatGPT agent
  -> custom MCP app
  -> OpenAI Secure MCP Tunnel
  -> tunnel-client on your computer
  -> http://127.0.0.1:3001/mcp
  -> x-mcp-server
  -> official X API

The X credentials stay local. ChatGPT connects to the local MCP server through the tunnel; it does not receive your X access tokens.

Available MCP Tools

Tool

Type

Description

x_get_active_account

Read

Returns the selected local profile, configured accounts, auth provider, mode, and authenticated X user.

x_get_me

Read

Returns the authenticated X user.

x_get_user

Read

Looks up an X user by username.

x_get_post

Read

Reads a post by ID.

x_get_user_posts

Read

Lists recent posts authored by a user ID.

x_search_posts

Read

Searches recent posts using the official X query syntax.

x_create_post

Write

Publishes a new post. Requires X_MCP_MODE=read-write.

x_reply_post

Write

Replies to a post. Requires X_MCP_MODE=read-write.

Write tools are blocked unless X_MCP_MODE=read-write is set.

Requirements

  • Node.js 20 or newer.

  • An X Developer account.

  • An X Developer App with OAuth 2.0 enabled.

  • X read scopes: tweet.read users.read.

  • X write scope for publishing and replies: tweet.write.

  • Recommended X token manager: X's official xurl CLI.

  • For ChatGPT: Developer Mode enabled.

  • For ChatGPT local connections: an OpenAI Secure MCP Tunnel and tunnel-client.

Step-by-Step Installation

1. Clone the Repository

git clone https://github.com/lluisfont/x-mcp-server.git
cd x-mcp-server

If you already have the repository:

cd C:\Repos\x-mcp-server
git pull

2. Install Dependencies

npm install

3. Create a Local Environment File

Copy-Item .env.example .env

Edit .env locally.

Do not commit .env. It may contain local app names, usernames, access tokens, refresh tokens, client secrets, and private API keys.

4. Configure the Active X Account

Recommended setup: use xurl as the token manager.

X_AUTH_PROVIDER=xurl
X_XURL_APP=fcbnews
X_XURL_USERNAME=FCBNews2026
X_MCP_ACCOUNT=fcbnews2026
X_MCP_MODE=read-only
X_API_BASE_URL=https://api.x.com

Configure xurl once outside this project:

$secret = Read-Host "X OAuth Client Secret" -AsSecureString
$plain = [Runtime.InteropServices.Marshal]::PtrToStringAuto(
  [Runtime.InteropServices.Marshal]::SecureStringToBSTR($secret)
)
npx -y @xdevplatform/xurl auth apps add fcbnews --client-id "<OAuth 2.0 Client ID>" --client-secret $plain --redirect-uri http://localhost:8080/callback
npx -y @xdevplatform/xurl auth oauth2 --app fcbnews FCBNews2026

Register this callback URI in the X Developer App:

http://localhost:8080/callback

xurl stores tokens in its own local store and refreshes/persists them when needed. The MCP server calls:

npx -y @xdevplatform/xurl token --app fcbnews -u FCBNews2026

Legacy direct-token setup is still available with X_AUTH_PROVIDER=env:

X_AUTH_PROVIDER=env
X_MCP_ACCOUNT=fcbnews2026
X_MCP_MODE=read-only

X_ACCOUNT_FCBNEWS2026_USER_ACCESS_TOKEN=
X_ACCOUNT_FCBNEWS2026_REFRESH_TOKEN=

X_ACCOUNT_LLUISFONT_USER_ACCESS_TOKEN=
X_ACCOUNT_LLUISFONT_REFRESH_TOKEN=

The legacy single-account env-token mode is also supported:

X_AUTH_PROVIDER=env
X_MCP_ACCOUNT=default
X_USER_ACCESS_TOKEN=

New installations should prefer X_AUTH_PROVIDER=xurl.

5. Choose the Transport

For local MCP hosts that start the process directly:

X_MCP_TRANSPORT=stdio

For ChatGPT through a local tunnel:

X_MCP_TRANSPORT=http
X_MCP_HTTP_PORT=3001
X_MCP_HTTP_PATH=/mcp

6. Run Type Checks and Tests

npm run typecheck
npm test
npm run build

7. Start the MCP Server

For stdio:

npm run dev

For local HTTP:

npm run dev:http

The default HTTP MCP endpoint is:

http://127.0.0.1:3001/mcp

Health check:

Invoke-RestMethod http://127.0.0.1:3001/healthz | ConvertTo-Json -Compress

Expected response:

{"ok":true,"transport":"http","activeAccount":"fcbnews2026","mode":"read-only"}

Local MCP Server Lifecycle

When ChatGPT uses this MCP through a tunnel, two local processes must be running:

1. The MCP HTTP server
   -> npm run dev:http
   -> http://127.0.0.1:3001/mcp

2. tunnel-client
   -> .\.tools\tunnel-client\tunnel-client.exe run --profile <profile>
   -> OpenAI Secure MCP Tunnel

If either process is stopped, ChatGPT cannot use the MCP tools.

Start Manually

Terminal 1:

cd C:\Repos\x-mcp-server
npm run dev:http

Terminal 2:

cd C:\Repos\x-mcp-server
.\.tools\tunnel-client\tunnel-client.exe run --profile x-fcbnews

Keep both terminals open.

Verify Local Availability

Check the MCP server:

Invoke-RestMethod http://127.0.0.1:3001/healthz | ConvertTo-Json -Compress

Check the tunnel client:

Invoke-WebRequest http://127.0.0.1:8080/readyz -UseBasicParsing

The tunnel readiness endpoint should return HTTP 200.

Stop Manually

Press Ctrl+C in:

  • The terminal running npm run dev:http.

  • The terminal running tunnel-client run.

Once both are stopped, ChatGPT no longer has access to the local MCP server.

Change Account or Safety Mode

Edit .env.

Change active account:

X_MCP_ACCOUNT=fcbnews2026

Enable write mode:

X_MCP_MODE=read-write

Return to safe read-only mode:

X_MCP_MODE=read-only

Restart the MCP HTTP server after changing .env:

Ctrl+C
npm run dev:http

The tunnel can remain running if the local port and MCP path did not change.

Start Automatically on Windows Login

For a computer that should regularly host this MCP, use Windows Task Scheduler.

Create a local startup script, for example:

C:\Users\<user>\mcp-start\x-fcbnews-start.ps1

Script:

$repo = "C:\Repos\x-mcp-server"
$profile = "x-fcbnews"

Set-Location $repo

Start-Process powershell.exe -ArgumentList @(
  "-NoExit",
  "-ExecutionPolicy", "Bypass",
  "-Command", "cd `"$repo`"; npm run dev:http"
) -WindowStyle Minimized

Start-Sleep -Seconds 5

Start-Process powershell.exe -ArgumentList @(
  "-NoExit",
  "-ExecutionPolicy", "Bypass",
  "-Command", "cd `"$repo`"; .\.tools\tunnel-client\tunnel-client.exe run --profile $profile"
) -WindowStyle Minimized

Register the scheduled task:

$action = New-ScheduledTaskAction `
  -Execute "powershell.exe" `
  -Argument "-ExecutionPolicy Bypass -File `"C:\Users\<user>\mcp-start\x-fcbnews-start.ps1`""

$trigger = New-ScheduledTaskTrigger -AtLogOn

Register-ScheduledTask `
  -TaskName "X MCP FCBNews2026" `
  -Action $action `
  -Trigger $trigger `
  -Description "Starts the local X MCP server and OpenAI tunnel-client at Windows logon."

Disable automatic startup:

Disable-ScheduledTask -TaskName "X MCP FCBNews2026"

Enable it again:

Enable-ScheduledTask -TaskName "X MCP FCBNews2026"

Delete it:

Unregister-ScheduledTask -TaskName "X MCP FCBNews2026" -Confirm:$false

Full lifecycle guide:

docs/local-server-lifecycle.md

Connect to ChatGPT

High-level flow:

1. Run the MCP server over local HTTP.
2. Create a tunnel in OpenAI Platform.
3. Create a local tunnel-client profile pointing to http://127.0.0.1:3001/mcp.
4. Start tunnel-client.
5. Create a custom MCP app in the ChatGPT agent using Connection: Tunnel.
6. Test x_get_active_account or x_get_me before any write operation.

Recommended ChatGPT custom MCP settings:

Connection: Tunnel
Tunnel: <your OpenAI tunnel>
Authentication: No authentication

Use No authentication when the MCP server manages the final service credentials locally, for example through .env.

Full ChatGPT setup guide:

docs/chatgpt-mcp-setup.md

Reauthorize an X Account

Recommended xurl flow:

npx -y @xdevplatform/xurl auth oauth2 --app fcbnews FCBNews2026

Use the legacy helper only for X_AUTH_PROVIDER=env:

$env:X_OAUTH_CLIENT_ID = "<OAuth 2.0 Client ID>"
$env:X_MCP_ACCOUNT = "fcbnews2026"
npm run x:oauth

Restart the MCP server after reauthorization:

npm run dev:http

Then verify with:

x_get_active_account

Detailed OAuth guide:

docs/x-oauth.md

Safety Model

The server starts in read-only mode by default:

X_MCP_MODE=read-only

Write tools require:

X_MCP_MODE=read-write

Before publishing:

  • Verify the active account with x_get_active_account.

  • Confirm the exact text to publish.

  • Ensure the X token has tweet.write.

  • Prefer X_AUTH_PROVIDER=xurl so X token refresh and rotation are handled by X's official CLI.

  • Ask the agent to return the generated post_id.

  • Do not treat a post as published until X returns an ID.

Scripts

Script

Purpose

npm run dev

Starts the MCP server over stdio.

npm run dev:http

Starts the MCP server over local HTTP.

npm run x:oauth

Runs the local X OAuth authorization helper.

npm run build

Compiles TypeScript to dist.

npm run start

Starts the compiled server over stdio.

npm run start:http

Starts the compiled server over HTTP.

npm run typecheck

Runs TypeScript without emitting files.

npm test

Runs the Vitest test suite.

Documentation

Operational Security

  • Keep credentials outside Git.

  • Keep read-only as the default mode.

  • Enable read-write only for controlled workflows.

  • Verify the active account before publishing.

  • Do not log access tokens or refresh tokens.

  • Do not paste tokens into chats, issues, docs, or pull requests.

  • Do not run automatic startup in read-write mode on shared computers.

License

No open-source license has been selected yet.

Available Tools

8 tools
x_create_postB

Publish a new X post. Requires X_MCP_MODE=read-write and tweet.write scope.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYes

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the write/non-destructive profile is covered. The description adds genuine behavioral context by naming the required server mode and OAuth scope, but says nothing about idempotency, rate limits, or what the call returns.

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

Conciseness5/5

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

Two short sentences, zero filler, with the action front-loaded and the prerequisite immediately after. Every clause carries information.

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

Completeness3/5

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

Prerequisites are covered, but with no output schema and an undocumented parameter, the definition leaves the agent guessing about the payload shape and the response. Adequate for a simple publish action but with clear gaps.

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

Parameters2/5

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

Schema description coverage is 0% for the single required 'text' parameter, and the description never mentions it. No content format, mention/link handling, or length constraints are conveyed beyond the bare minLength/maxLength in the schema.

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 uses a specific verb+resource ('Publish a new X post'), which is unambiguous and distinguishable from the read-oriented siblings (x_get_post, x_search_posts). It does not explicitly contrast with x_reply_post, the other write sibling, so it stops short of a 5.

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

Usage Guidelines3/5

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

It states prerequisites (X_MCP_MODE=read-write, tweet.write scope), which implies context of use, but gives no explicit when-to-use versus x_reply_post or when-not guidance. Useful but inferential rather than directive.

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

x_get_active_accountA
Read-only

Get the local X account profile selected for this MCP server installation. Does not expose tokens.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.7/5.0
Behavior4/5

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

readOnlyHint=true already establishes the safety profile, so the bar is lower, and the description adds a genuine security-relevant disclosure: 'Does not expose tokens.' That is useful context beyond the annotation. It does not describe return contents, but the token caveat is the meaningful addition.

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

Conciseness5/5

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

Two short sentences, no filler, with the resource identity front-loaded and the security caveat in the second clause. Nothing extraneous.

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?

For a zero-parameter read-only tool with annotations covering safety, this is nearly complete. The only missing piece is a hint about what profile fields come back, which matters slightly since no output schema exists.

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

Parameters4/5

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

Zero parameters, so the baseline is 4 by rule. There is no parameter surface for the description to clarify or obscure.

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?

States a specific verb and resource ('Get the local X account profile') and scopes it to the account selected for this installation. It is largely distinguishable from siblings, though the boundary with x_get_me is not spelled out in the description itself.

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?

No guidance on when to use this versus x_get_me or x_get_user, which is the most likely confusion given the near-identical resource. The agent has to infer the distinction from the name alone.

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

x_get_meB
Read-only

Get the authenticated X user.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.4/5.0
Behavior3/5

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

The readOnlyHint=true annotation already establishes this is a safe read, so the description's main added value is the 'authenticated' scoping, which implies auth is required and no user id is passed. It says nothing about what identity fields come back or what happens if the token is invalid.

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

Conciseness5/5

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

A single front-loaded sentence with no filler. Every word carries information.

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

Completeness3/5

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

For a parameterless read with annotations covering the safety profile, this is nearly sufficient, but the ambiguity against x_get_user and x_get_active_account is unresolved and no return-shape hint is given (there is no output schema).

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

Parameters4/5

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

Zero parameters, so there is nothing for the description to clarify; baseline 4 applies. The description correctly implies the user is derived from the authenticated session rather than passed in.

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?

States a specific verb and resource ('get the authenticated X user'), which is meaningful against siblings like x_get_user and x_get_active_account. However, it does not explicitly distinguish itself from those overlapping siblings, so the reader must infer the difference.

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?

No guidance on when to use this versus x_get_user or x_get_active_account, both of which plausibly return user data. The agent is left to infer the distinction from the word 'authenticated' alone.

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

x_get_postB
Read-only

Get a single X post by ID.

ParametersJSON Schema
NameRequiredDescriptionDefault
postIdYes

TDQS

B3.4/5.0
Behavior3/5

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

The readOnlyHint annotation already declares this as a safe read, so the description's remaining burden is lower. It adds little beyond the annotation: no mention of auth requirements, deleted/protected post behavior, or rate limits. A 3 reflects that annotations carry the safety profile while the description adds almost nothing.

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

Conciseness5/5

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

A single, front-loaded sentence with zero waste. Appropriate for a simple lookup tool.

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

Completeness3/5

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

For a basic read-by-ID tool with annotations covering safety, this is minimally adequate. Missing are edge-case behavior, format of the ID, and sibling differentiation, leaving some gaps for an agent choosing among post-related tools.

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

Parameters4/5

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

There is only one parameter, so the baseline is 4. Schema coverage is 0% and the description only restates 'by ID', but with a single obvious parameter the description is adequate.

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 states a specific verb and resource: retrieving a single X post by ID. It is clear on its own, but it offers no distinction from siblings like x_search_posts or x_get_user_posts, which also return post data.

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?

There is no guidance on when to use this tool versus x_search_posts or x_get_user_posts. The word 'single' implies an exact-ID lookup, but this is not explicit and no alternatives or exclusions are named.

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

x_get_userC
Read-only

Get an X user by username.

ParametersJSON Schema
NameRequiredDescriptionDefault
usernameYesUsername without @

TDQS

C2.9/5.0
Behavior2/5

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

readOnlyHint=true already tells the agent this is a safe read, and the description adds nothing further: no failure behavior for unknown usernames, no note on what user data is returned, no authentication context. It restates the operation rather than disclosing behavior.

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?

A single front-loaded sentence with no filler. It is appropriately sized for a one-parameter lookup, though it is arguably too sparse to be maximally useful.

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

Completeness3/5

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

For a simple one-param read with annotations covering safety and full schema coverage, the essentials are present. Still missing is any signal about return content or how to distinguish this from x_get_me and x_get_active_account.

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%, including the useful 'Username without @' constraint, so the schema carries full parameter meaning. The description adds nothing beyond that, which is the expected baseline when the schema does the work.

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 states a specific verb and resource ('Get an X user by username'), so its function is unambiguous. However, it does not distinguish itself from close siblings like x_get_me or x_get_active_account, leaving the agent to infer which retrieval path applies.

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?

There is no when-to-use guidance and no mention of alternatives. With siblings that also return users (x_get_me, x_get_active_account), the definition provides no basis for choosing between them.

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

x_get_user_postsC
Read-only

Get recent posts authored by an X user ID.

ParametersJSON Schema
NameRequiredDescriptionDefault
userIdYes
maxResultsNo

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds one useful behavioral trait, that only 'recent' posts are returned (not full history), but it never defines that window or says anything about pagination or ordering.

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?

A single front-loaded sentence with no wasted words. It is efficient, though arguably under-specified rather than optimally concise.

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

Completeness2/5

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

For a low-complexity two-parameter tool with no output schema, an agent still lacks what 'recent' means, how many posts come back, whether the list is paginated, and what fields are returned. The definition is too thin to call correctly with confidence.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, yet it only restates that userId is an X user ID. maxResults is entirely unaddressed in the description; the schema supplies default/min/max but no meaning for the value or how results are paged.

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?

Names a specific verb and resource ('Get recent posts authored by an X user ID'), so the agent knows exactly what is retrieved. It does not distinguish itself from siblings like x_search_posts or x_get_post, but the by-user scoping is still clear.

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?

No when-to-use guidance, no mention of alternatives (e.g. x_search_posts for query-based retrieval, x_get_post for a single post), and no prerequisites such as requiring a user ID from x_get_user or x_get_me.

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

x_reply_postA

Reply to an X post. Requires X_MCP_MODE=read-write and tweet.write scope.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYes
postIdYes

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already establish this is a non-read-only, non-destructive write. The description adds the auth/config requirement (mode and scope), which is genuine value beyond the annotations. It omits rate limits, whether the reply threads to the parent, and error/permission failure behavior.

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

Conciseness5/5

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

Two tight sentences with zero filler; the action is front-loaded and the prerequisite follows. Sized appropriately for a simple two-parameter tool.

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

Completeness3/5

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

No output schema exists, so the description should say what comes back, and it doesn't. Combined with undocumented parameters and no sibling differentiation, the definition is adequate but leaves real gaps for a write tool.

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?

Two required parameters with 0% schema description coverage, so the schema alone explains nothing about 'text' (reply body) or 'postId' (target post). The description mentions replying to 'a post' but does not map either parameter or note the 25000-char limit implied by the schema.

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?

Names a specific verb+resource ('Reply to an X post'), which is unambiguous on its own. It does not differentiate from the closely related sibling x_create_post (a reply is a kind of post creation), leaving the agent to infer the boundary.

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

Usage Guidelines3/5

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

Gives a real precondition (X_MCP_MODE=read-write and tweet.write scope), which is useful operational guidance. It says nothing about when to prefer this over x_create_post or x_get_post, and no exclusions are stated, so usage is only partially covered.

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

x_search_postsC
Read-only

Search recent X posts using the official X query syntax.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
maxResultsNo

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already establish readOnlyHint=true, so the safety profile is covered. The description adds one genuine behavioral fact — results are limited to 'recent' posts, not the full archive — but says nothing about rate limits, authentication requirements, result volume, or how results are ordered, leaving meaningful behavioral gaps for a search tool.

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?

A single front-loaded sentence with no wasted words. It is efficiently sized, though the extreme brevity is part of why other dimensions are thin.

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

Completeness2/5

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

With no output schema, 0% parameter description coverage, and only a readOnlyHint annotation, the description would need to carry most of the load. Instead it omits the query syntax details, the meaning of maxResults, and any sense of the returned result shape, so an agent cannot call this confidently without outside knowledge.

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

Parameters2/5

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

Schema description coverage is 0%, so both parameters are undocumented in the schema. The description nods at 'official X query syntax' for the query parameter but gives no operators, examples, or format rules, and it says nothing at all about maxResults (its default of 10, its 10-100 range, or how it interacts with the query).

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?

States a specific verb ('Search') and resource ('recent X posts'), which is clear on its face. It does not, however, distinguish itself from siblings such as x_get_user_posts or x_get_post, which also return posts, so the agent must infer the distinction from the verb alone.

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?

There is no explicit when-to-use guidance, no conditions or exclusions, and no reference to the sibling tools that also retrieve posts. The word 'recent' implies a temporal scope but the description never tells the agent when search is preferable to x_get_user_posts or x_get_post.

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.

  1. 8 tool updatesv0.1.0
    • First observedx_create_post
    • First observedx_get_active_account
    • First observedx_get_me
    • First observedx_get_post
    • First observedx_get_user
    • First observedx_get_user_posts
    • First observedx_reply_post
    • First observedx_search_posts

TDQS

B3.4/5.0

Scored across 8 tools

Disambiguation4/5

Tools have largely distinct purposes: get_active_account (local config) vs get_me (authenticated API user) vs get_user (by username) are differentiated by descriptions, and get_post vs get_user_posts vs search_posts are clearly separated. Minor potential confusion among the three user-retrieval tools, but descriptions resolve it adequately.

Naming Consistency5/5

All tools follow a consistent snake_case pattern with an x_ prefix and verb_noun structure (e.g., x_get_user, x_create_post, x_reply_post). No deviations in style or convention.

Tool Count5/5

Eight tools is well-scoped for a focused X API server covering basic read and write operations. Each tool earns its place, with no redundant or excessive entries.

Completeness3/5

The surface covers reading posts/users and creating posts/replies, but notable gaps exist: no delete or edit post, no like/retweet, and no follow/unfollow. These missing operations limit common agent workflows.

Maintenance

ActivitySlowing
ResponsivenessNo issues

Related MCP Connectors

  • Twitter/X read-only MCP server — 12 tools: search, users, tweets, followers, timelines, trends.

  • X (Twitter) data for AI agents: tweets, profiles, followers, search, trends + social listening.

  • Your agent needs X/Twitter data — who follows a competitor, what a community is posting, who quoted that tweet, what is trending in Japan. Normally that means applying for an X developer account, passing app review, and managing a quota per endpoint. **What you can ask for** • "Who follows @stripe, and which of them are verified?" • "Pull every reply and quote on this tweet and summarise what people object to." • "List this community's moderators and its posts this week." • "What is trending in Japan right now?" • "Give me the full thread context behind this link, including the long-form article." **How to use it** Point any MCP client at https://mcp.aisa.one/twitter-api/mcp and sign in with OAuth — there is no key to create or paste. 29 read tools: users (profile, about, batch lookup by id, search, followers, verified followers, followings, follow check), tweets (timeline, latest, mentions, advanced search, replies, quotes, retweeters, thread context, articles), communities, lists, Spaces and trends. **Why this rather than the source** No developer account to apply for, no app review, no per-endpoint quota to manage. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Ask for a handle's followers here, then ask the same agent for that brand's search traffic, its backlinks, or the people to contact — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/social/mcp for X plus Instagram, Reddit, Pinterest and YouTube; https://mcp.aisa.one/gtm/mcp for those plus Similarweb and Apollo.

  • X (formerly Twitter) posts, profiles, and search for AI agents. Free key, self-minted, no signup.

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