x-mcp-server
X MCP Server
TypeScript Model Context Protocol (MCP) server for the official X API.
Este proyecto permite a los agentes compatibles con MCP, incluidos los agentes de ChatGPT, leer de forma segura desde y publicar en cuentas de X mediante un servidor local que se ejecuta en tu propio ordenador.
El servidor admite:
Leer la cuenta de X autenticada.
Buscar usuarios de X por nombre de usuario.
Leer publicaciones por ID.
Listar publicaciones recientes de un usuario.
Buscar publicaciones recientes con la sintaxis de búsqueda de X.
Crear publicaciones y respuestas cuando el modo de escritura está habilitado explícitamente.
Seleccionar una cuenta de X diferente por instalación local del ordenador.
Ejecutarse a través de
stdiopara hosts MCP locales.Ejecutarse a través de HTTP Streamable local para ChatGPT mediante OpenAI Secure MCP Tunnels.
Estado del Proyecto
Este es un MVP funcional.
Implementado:
Servidor MCP sobre
stdio.Servidor MCP sobre Streamable HTTP.
Cliente oficial de la API de X.
Configuración local de múltiples cuentas.
Modo seguro
read-onlypor defecto.Modo
read-writeexplícito para publicar y responder.Asistente local de OAuth 2.0 Authorization Code + PKCE para la reautorización de cuentas de X.
Pruebas unitarias con Vitest.
Guía de conexión de ChatGPT a través de OpenAI Secure MCP Tunnels.
Guía del ciclo de vida del servidor local para el inicio manual y automático en Windows.
Related MCP server: X API FastMCP Server
Cómo Funciona
Para hosts MCP locales:
MCP host
-> stdio
-> x-mcp-server
-> official X APIPara agentes de ChatGPT:
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 APILas credenciales de X permanecen locales. ChatGPT se conecta al servidor MCP local a través del túnel; no recibe tus tokens de acceso de X.
Herramientas MCP Disponibles
Tool | Tipo | Descripción |
| Lectura | Devuelve el perfil local seleccionado, las cuentas configuradas, el modo y el usuario de X autenticado. |
| Lectura | Devuelve el usuario de X autenticado. |
| Lectura | Busca un usuario de X por nombre de usuario. |
| Lectura | Lee una publicación por ID. |
| Lectura | Lista publicaciones recientes creadas por un ID de usuario. |
| Lectura | Busca publicaciones recientes utilizando la sintaxis de consulta oficial de X. |
| Escritura | Publica una nueva publicación. Requiere |
| Escritura | Responde a una publicación. Requiere |
Las herramientas de escritura están bloqueadas a menos que se establezca X_MCP_MODE=read-write.
Requisitos
Node.js 20 o superior.
Una cuenta de X Developer.
Una aplicación X Developer con OAuth 2.0 habilitado.
Ámbitos de lectura de X:
tweet.read users.read.Ámbito de escritura de X para publicar y responder:
tweet.write.Ámbito de actualización recomendado de X:
offline.access.Para ChatGPT: modo desarrollador habilitado.
Para conexiones locales de ChatGPT: un OpenAI Secure MCP Tunnel y
tunnel-client.
Instalación Paso a Paso
1. Clonar el Repositorio
git clone https://github.com/lluisfont/x-mcp-server.git
cd x-mcp-serverSi ya tienes el repositorio:
cd C:\Repos\x-mcp-server
git pull2. Instalar Dependencias
npm install3. Crear un Archivo de Entorno Local
Copy-Item .env.example .envEdita .env localmente.
No hagas commit de .env. Puede contener tokens de acceso, tokens de actualización,
secretos de cliente y claves API privadas.
4. Configurar la Cuenta de X Activa
Para una cuenta local con nombre:
X_MCP_ACCOUNT=fcbnews2026
X_MCP_MODE=read-only
X_API_BASE_URL=https://api.x.com
X_ACCOUNT_FCBNEWS2026_USER_ACCESS_TOKEN=
X_ACCOUNT_FCBNEWS2026_REFRESH_TOKEN=Para múltiples cuentas en el mismo ordenador:
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=X_MCP_ACCOUNT selecciona el perfil local utilizado por esta instalación. Diferentes
ordenadores pueden seleccionar diferentes cuentas sin cambiar código.
El modo heredado de cuenta única también es compatible:
X_MCP_ACCOUNT=default
X_USER_ACCESS_TOKEN=Las instalaciones nuevas deberían preferir cuentas con nombre.
5. Elegir el Transporte
Para hosts MCP locales que inician el proceso directamente:
X_MCP_TRANSPORT=stdioPara ChatGPT a través de un túnel local:
X_MCP_TRANSPORT=http
X_MCP_HTTP_PORT=3001
X_MCP_HTTP_PATH=/mcp6. Ejecutar Comprobaciones de Tipos y Pruebas
npm run typecheck
npm test
npm run build7. Iniciar el Servidor MCP
Para stdio:
npm run devPara HTTP local:
npm run dev:httpEl endpoint HTTP MCP predeterminado es:
http://127.0.0.1:3001/mcpComprobación de salud:
Invoke-RestMethod http://127.0.0.1:3001/healthz | ConvertTo-Json -CompressRespuesta esperada:
{"ok":true,"transport":"http","activeAccount":"fcbnews2026","mode":"read-only"}Ciclo de Vida del Servidor MCP Local
Cuando ChatGPT usa este MCP a través de un túnel, deben estar ejecutándose dos procesos locales:
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 TunnelSi alguno de los procesos se detiene, ChatGPT no puede usar las herramientas MCP.
Iniciar Manualmente
Terminal 1:
cd C:\Repos\x-mcp-server
npm run dev:httpTerminal 2:
cd C:\Repos\x-mcp-server
.\.tools\tunnel-client\tunnel-client.exe run --profile x-fcbnewsMantén ambas terminales abiertas.
Verificar Disponibilidad Local
Comprueba el servidor MCP:
Invoke-RestMethod http://127.0.0.1:3001/healthz | ConvertTo-Json -CompressComprueba el cliente de túnel:
Invoke-WebRequest http://127.0.0.1:8080/readyz -UseBasicParsingEl endpoint de disponibilidad del túnel debería devolver HTTP 200.
Detener Manualmente
Pulsa Ctrl+C en:
La terminal que ejecuta
npm run dev:http.La terminal que ejecuta
tunnel-client run.
Una vez detenidos ambos, ChatGPT ya no tiene acceso al servidor MCP local.
Cambiar Cuenta o Modo de Seguridad
Edita .env.
Cambiar cuenta activa:
X_MCP_ACCOUNT=fcbnews2026Habilitar modo de escritura:
X_MCP_MODE=read-writeVolver al modo seguro de solo lectura:
X_MCP_MODE=read-onlyReinicia el servidor HTTP MCP después de cambiar .env:
Ctrl+C
npm run dev:httpEl túnel puede permanecer en ejecución si el puerto local y la ruta MCP no cambiaron.
Iniciar Automáticamente al Iniciar Sesión en Windows
Para un ordenador que deba alojar este MCP regularmente, usa el Programador de tareas de Windows.
Crea un script de inicio local, por ejemplo:
C:\Users\<user>\mcp-start\x-fcbnews-start.ps1Script:
$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 MinimizedRegistra la tarea programada:
$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 $trigger `
-Description "Starts the local X MCP server and OpenAI tunnel-client at Windows logon."Deshabilitar el inicio automático:
Disable-ScheduledTask -TaskName "X MCP FCBNews2026"Habilitarlo de nuevo:
Enable-ScheduledTask -TaskName "X MCP FCBNews2026"Eliminarlo:
Unregister-ScheduledTask -TaskName "X MCP FCBNews2026" -Confirm:$falseGuía completa del ciclo de vida:
docs/local-server-lifecycle.md
Conectar a ChatGPT
Flujo de alto nivel:
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.Configuración MCP personalizada recomendada para ChatGPT:
Connection: Tunnel
Tunnel: <your OpenAI tunnel>
Authentication: No authenticationUsa No authentication cuando el servidor MCP gestione las credenciales finales del servicio
localmente, por ejemplo a través de .env.
Guía completa de configuración de ChatGPT:
Reautorizar una Cuenta de X
En X Developer, configura la aplicación:
OAuth 2.0: Enabled
App permissions: Read and write
Callback URI: http://127.0.0.1:3002/callback
Website URL: http://127.0.0.1:3002Ejecuta:
$env:X_OAUTH_CLIENT_ID = "<OAuth 2.0 Client ID>"
$env:X_MCP_ACCOUNT = "fcbnews2026"
npm run x:oauthAbre la URL generada mientras tengas la sesión iniciada en la cuenta de X deseada. Después de la
autorización, el asistente actualiza .env con el token de la cuenta seleccionada.
Reinicia el servidor MCP después de la reautorización:
npm run dev:httpLuego verifica con:
x_get_active_accountGuía detallada de OAuth:
Modelo de Seguridad
El servidor se inicia en modo de solo lectura por defecto:
X_MCP_MODE=read-onlyLas herramientas de escritura requieren:
X_MCP_MODE=read-writeAntes de publicar:
Verifica la cuenta activa con
x_get_active_account.Confirma el texto exacto a publicar.
Asegúrate de que el token de X tenga
tweet.write.Pide al agente que devuelva el
post_idgenerado.No consideres una publicación como publicada hasta que X devuelva un ID.
Scripts
Script | Propósito |
| Inicia el servidor MCP a través de |
| Inicia el servidor MCP a través de HTTP local. |
| Ejecuta el asistente local de autorización OAuth de X. |
| Compila TypeScript a |
| Inicia el servidor compilado a través de |
| Inicia el servidor compilado a través de HTTP. |
| Ejecuta TypeScript sin emitir archivos. |
| Ejecuta el conjunto de pruebas de Vitest. |
Documentación
docs/project-architecture.md: arquitectura del proyecto.
docs/configuration.md: variables de entorno y configuración de múltiples cuentas.
docs/local-server-lifecycle.md: iniciar, detener y automatizar el servidor MCP local.
docs/tools.md: herramientas MCP y contratos de uso.
docs/x-oauth.md: reautorización OAuth de X.
docs/development.md: pautas de desarrollo, pruebas y cambios.
docs/chatgpt-mcp-setup.md: configuración paso a paso de ChatGPT MCP.
Seguridad Operativa
Mantén las credenciales fuera de Git.
Mantén
read-onlycomo modo predeterminado.Habilita
read-writesolo para flujos de trabajo controlados.Verifica la cuenta activa antes de publicar.
No registres tokens de acceso ni tokens de actualización.
No pegues tokens en chats, issues, documentos ni pull requests.
No ejecutes el inicio automático en modo
read-writeen ordenadores compartidos.
Licencia
Aún no se ha seleccionado una licencia de código abierto.
Available Tools
8 toolsx_create_postB
Publish a new X post. Requires X_MCP_MODE=read-write and tweet.write scope.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
TDQS
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.
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.
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.
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.
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.
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_accountARead-only
Get the local X account profile selected for this MCP server installation. Does not expose tokens.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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.
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.
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.
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.
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.
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_meBRead-only
Get the authenticated X user.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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.
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.
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.
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.
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.
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_postBRead-only
Get a single X post by ID.
| Name | Required | Description | Default |
|---|---|---|---|
| postId | Yes |
TDQS
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.
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.
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.
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.
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.
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_userCRead-only
Get an X user by username.
| Name | Required | Description | Default |
|---|---|---|---|
| username | Yes | Username without @ |
TDQS
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.
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.
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.
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.
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.
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_postsCRead-only
Get recent posts authored by an X user ID.
| Name | Required | Description | Default |
|---|---|---|---|
| userId | Yes | ||
| maxResults | No |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| postId | Yes |
TDQS
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.
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.
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.
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.
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.
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_postsCRead-only
Search recent X posts using the official X query syntax.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| maxResults | No |
TDQS
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.
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.
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.
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.
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.
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.
8 tool updates
v0.1.0- First observed
x_create_post - First observed
x_get_active_account - First observed
x_get_me - First observed
x_get_post - First observed
x_get_user - First observed
x_get_user_posts - First observed
x_reply_post - First observed
x_search_posts
TDQS
Scored across 8 tools
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.
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.
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.
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
Related MCP Connectors
Hosted X (Twitter) MCP server for Claude, ChatGPT and Cursor, with each action switched per account.
Twitter/X read-only MCP server — 12 tools: search, users, tweets, followers, timelines, trends.
Official twitterapi.io hosted MCP: Twitter/X tweets, users, followers, trends. OAuth or API key.
Official MCP server for twitterapis.com. Read and write Twitter/X: search, users, tweets, DMs.
Related MCP Servers
- AlicenseAqualityDmaintenanceAn MCP server that provides AI agents with full access to the X (Twitter) API for posting, searching, and managing engagement through natural language. It supports comprehensive tools for tweet management, media uploads, and account analytics across multiple MCP-compatible clients.1557MIT

X API FastMCP Serverofficial
FlicenseNot gradedqualityFmaintenanceA local MCP server that exposes the X API (formerly Twitter API) as tools, enabling operations like posting, searching, user management, and more via natural language commands.865-- AlicenseAqualityCmaintenanceMCP server for Twitter/X enabling AI agents to search, post, reply, and engage with tweets.143 npm2MIT
- AlicenseAqualityAmaintenanceMCP server for the Twitter/X API, enabling search, user profiles, tweets, followers, and more via natural language.94286 npm4MIT