PostMCP MCP Server
OfficialPostMCP AI Model Context Protocol (MCP) Server
Offizieller PostMCP AI Model Context Protocol (MCP) Server. Verbinden Sie Ihre Social-Media-Publishing-Pipelines direkt mit KI-Assistenten, Desktop-Anwendungen, IDE-Workflows und Web-Umgebungen wie Claude Desktop, Claude.ai, Cursor und ChatGPT Custom GPTs.
Unterstützte Plattformen sind LinkedIn, X (Twitter), Facebook, Instagram, Threads und Bluesky.
🚀 Funktionen & Fähigkeiten
🤖 15 integrierte Tools: Workspaces, verbundene Konten und deren Token-Status, Brand Kits, die Post-Warteschlange, Pre-Flight-Checks, Erstellen/Planen/Neuplanen/Veröffentlichen/Wiederholen/Löschen sowie Bildgenerierung.
⚡ Duale Transportmodi: Nativer Stdio-Modus (für lokale Desktop-Apps & IDEs) und Streamable-HTTP-Modus (für Webdienste, Claude.ai und Remote-Connectors).
🔑 Flexible Authentifizierung: Erkennt den API-Schlüssel automatisch aus Umgebungsvariablen (
POSTMCPAI_API_KEY), URL-Abfrageparametern (?apikey=YOUR_KEY) oder HTTP-Autorisierungs-Headern (x-api-key,Bearer token).🗂️ Multi-Workspace-fähig: Der API-Schlüssel trägt seinen eigenen Workspace, daher reicht ein nackter Schlüssel. Um auf einen anderen Workspace zu wirken, akzeptiert jedes Tool eine optionale
workspaceId, die auch pro Verbindung (?projectId=...,x-project-id) oder pro Prozess (POSTMCPAI_PROJECT_ID) gesetzt werden kann.🤖 ChatGPT-Actions-kompatibel: Enthält einen integrierten OpenAPI-3.0-Spezifikationsgenerator (
/openapi.json) und REST-Endpunkte (/api/tools/:name) für die ChatGPT-Custom-GPT-Integration.🔒 OAuth-2.0- und RFC-9728-Unterstützung: Bewirbt PKCE-Autorisierungsserver-Metadaten für eine nahtlose dynamische Client-Registrierung mit Claude.ai.
Related MCP server: @posteverywhere/mcp
📁 Repository-Architektur
mcp-server/
├── bin/
│ └── cli.js # Executable CLI entry point (Stdio / HTTP mode runner)
├── src/
│ ├── config.js # Centralized configuration & environment loader
│ ├── client.js # Backend API client, API key & workspace extraction
│ ├── platforms.js # Platform limits, credit pricing & post cost helper
│ ├── tools/
│ │ ├── definitions.js# MCP tool JSON schemas & parameter specifications
│ │ ├── handlers.js # MCP tool execution handlers
│ │ └── index.js # Tool definitions aggregator
│ ├── server.js # MCP Server instance factory
│ ├── routes/
│ │ ├── oauth.js # OAuth 2.0 & RFC 9728 discovery endpoints
│ │ ├── openapi.js # OpenAPI 3.0 schema & ChatGPT REST endpoints
│ │ ├── mcpHttp.js # MCP Streamable HTTP transport (/mcp)
│ │ └── health.js # Health check & system metadata endpoints
│ ├── app.js # Express application factory
│ └── index.js # Main library entry point
├── index.js # Executable wrapper script
├── package.json
└── README.md⚙️ Umgebungskonfiguration
Umgebungsvariable | Beschreibung | Standardwert |
| Erforderlich. Ihr geheimer API-Schlüssel aus dem PostMCP-AI-Dashboard. |
|
| Die API-Root-URL Ihres PostMCP-AI-Backend-Dienstes. |
|
| Optional. Überschreibt den Workspace, an den der API-Schlüssel gebunden ist. Wird wiederum durch die | Der Workspace, aus dem der API-Schlüssel ausgestellt wurde |
| Wenn gesetzt, startet der Server im Remote-Streamable-HTTP-Modus. |
|
🛠️ MCP-Tools-Referenz
Jedes unten aufgeführte Tool akzeptiert außerdem eine optionale workspaceId (aus list_workspaces), um auf einen bestimmten Workspace zu wirken.
Lesen
Tool-Name | Beschreibung | Erforderlich | Optional |
| Authentifizierter Benutzer: Plan, Guthaben, KI-Tokens, aktiver Workspace und Rolle. | — |
|
| Jeder Workspace, dem der Benutzer angehört, mit IDs, Rollen und verbundenen Plattformen. | — | — |
| Verbundene Social-Profile mit der | — |
|
| Verbindungen, deren Token abgelaufen ist oder kurz davor steht und die neu verbunden werden müssen. | — |
|
| Brand Kits: Ton, Zielgruppe, Keywords, Stilbilder. | — |
|
| Post-Warteschlange, neueste zuerst, mit Lieferstatus pro Profil, Paginierung und Zählern. | — |
|
| Ein vollständiger Post: welche Profile ihn erhalten haben, Live-URLs und Fehler pro Profil. |
| — |
Schreiben
Tool-Name | Beschreibung | Erforderlich | Optional |
| Probelauf: Zeichenlimits, nicht verbundene Profile, fehlende Medien, Guthabenkosten. Veröffentlicht nichts. |
|
|
| Entwurf, Planung oder sofortige Veröffentlichung eines Posts an benannte Profile. Jedes Profil wird zu einem eigenen Post mit eigener ID. |
|
|
| Veröffentlicht einen vorhandenen Post sofort; wiederholt auch einen fehlgeschlagenen Post und überspringt dabei bereits belieferte Profile. |
| — |
| Aktualisiert Inhalt, Zielprofile, Zeitplan, Medien oder Status. |
|
|
| Verschiebt einen Post auf einen neuen Zeitpunkt und behält Text und Ziele bei. Aktiviert fehlgeschlagene und Entwurfs-Posts erneut. |
|
|
| Gibt einen mitten in der Veröffentlichung hängengebliebenen Post frei, damit er erneut versucht werden kann. Bereits belieferte Profile behalten ihren Status. |
|
|
| Bricht einen geplanten oder fehlgeschlagenen Post ab und löscht ihn. |
| — |
| Generiert ein Post-Bild und gibt dessen gehostete URL für |
|
|
Stapelverarbeitung
Tool-Name | Beschreibung | Erforderlich | Optional |
| Führt bis zu 20 der oben genannten Tools in einer Anfrage der Reihe nach aus. Tool-Namen werden validiert, bevor etwas ausgeführt wird, sodass ein Tippfehler nicht einen halben Stapel schreiben kann. Kann nicht verschachtelt werden. |
|
|
{
"calls": [
{ "id": "img", "tool": "generate_image", "arguments": { "prompt": "launch banner" } },
{
"tool": "create_post",
"arguments": {
"content": "We shipped it 🚀",
"targetAccounts": [
{ "platform": "linkedin", "profileId": "lin_7741903" },
{ "platform": "twitter", "profileId": "tw_1293847", "content": "We shipped it 🚀" }
],
"scheduleDate": "2026-09-01",
"scheduleTime": "10:00",
"timezone": "Asia/Kolkata"
}
}
],
"stopOnError": true
}Die Antwort enthält einen Eintrag pro Aufruf — { id, tool, ok, result } oder { id, tool, ok: false, error } — sowie Zähler und, wenn ein Fehler den Stapel gestoppt hat, die übersprungenen Aufrufe.
Hinweise für Clients
Profile ansprechen, nicht Plattformen.
targetAccountssendet nur an die genannten Profile;platformsverteilt an jedes verbundene Profil auf jeder Plattform.Ein Post pro Profil.
create_postspeichert einen separaten Post pro angesprochenem Profil, sodass jeder einzeln bearbeitet, wiederholt oder abgebrochen werden kann. Geben Sie profilbezogenen Text übertargetAccounts[].contentoder dievariants-Zuordnung an.Übergeben Sie immer
timezone, wenn eine Uhrzeit wichtig ist. Das Backend verwendet standardmäßig UTC, sodass ein um 9:00 IST geplanter Post ohne Zeitzone um 14:30 IST veröffentlicht wird.Guthaben werden pro beliefertem Profil berechnet (X/Twitter kostet 5, andere 1), plus einer einmaligen Zusatzgebühr von 50 Guthaben, wenn der Text einen Link enthält.
preflight_postmeldet dies, bevor Sie sich festlegen.
💻 Client-Integrationsanleitungen
1. Claude-Desktop-App (Stdio-Modus)
Fügen Sie die folgende Konfiguration zu Ihrer Claude-Desktop-Konfigurationsdatei hinzu:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"postmcpai": {
"command": "npx",
"args": ["-y", "@postmcpai/server"],
"env": {
"POSTMCPAI_API_KEY": "pmcp_sec_your_secret_api_key_here",
"POSTMCPAI_API_URL": "http://localhost:5023"
}
}
}
}2. Cursor IDE
Öffnen Sie Cursor Settings -> Features -> MCP.
Klicken Sie auf + Add New MCP Server.
Füllen Sie die Details aus:
Name:
postmcpaiType:
commandCommand:
npx -y @postmcpai/server
Fügen Sie unter Environment Variables hinzu:
POSTMCPAI_API_KEY=pmcp_sec_your_secret_api_key_herePOSTMCPAI_API_URL=http://localhost:5023
Klicken Sie auf Save.
3. Claude.ai & Remote-Web-Connectors (Streamable-HTTP-/SSE-Modus)
Hosten Sie diesen Server auf einem beliebigen Cloud-Dienst (Render, Railway, Fly.io, Vercel) oder tunneln Sie Ihre lokale Maschine mit ngrok.
Start im HTTP-Modus:
export POSTMCPAI_API_KEY="pmcp_sec_your_secret_api_key_here"
export POSTMCPAI_API_URL="https://your-backend-domain.com"
export PORT=3000
npm run start:sseVerbinden mit Claude.ai:
Geben Sie Ihre öffentliche MCP-URL mit angehängtem API-Schlüssel an:
https://your-hosted-domain.com/mcp?apikey=pmcp_sec_your_secret_api_key_hereClaude.ai erkennt die Tool-Fähigkeiten über
/mcpund authentifiziert sich nahtlos.Diese URL ist alles, was Sie brauchen: Der Schlüssel ist an den Workspace gebunden, aus dem er ausgestellt wurde, sodass Tools ohne weitere Angabe auf diesem Workspace wirken. Um denselben Schlüssel auf einen anderen Workspace auszurichten, hängen Sie
&projectId=YOUR_WORKSPACE_IDan (oder senden Sie einenx-project-id-Header); einzelne Tool-Aufrufe können beides weiterhin mitworkspaceIdüberschreiben.
4. ChatGPT Custom GPTs (REST-Aktionen)
Geben Sie bei der Konfiguration einer Custom GPT Action Ihre Server-URL an (z. B.
https://your-hosted-domain.com).Importieren Sie das OpenAPI-Schema direkt von:
https://your-hosted-domain.com/openapi.jsonSetzen Sie die Authentifizierung auf API Key (Header-Name:
Authorizationoderx-api-key).
5. Programmgestützte Node.js-Bibliotheksnutzung
Sie können @postmcpai/server auch als Bibliothek in Ihren eigenen Node.js-Backends verwenden:
import { createServer, createExpressApp, makeBackendRequest } from "@postmcpai/server";
// Create a standalone MCP Server instance
const mcpServer = createServer(() => process.env.POSTMCPAI_API_KEY);
// Or create an Express app with all remote routes attached
const app = createExpressApp();
app.listen(3000);🧪 Lokales Testen & Entwicklung
# Clone the repository
git clone https://github.com/postmcpai/postmcp-mcp-server.git
cd postmcp-mcp-server
# Install dependencies
npm install
# Start in Stdio Mode
npm start
# Start in HTTP Mode with hot reload
npm run dev📄 Lizenz
Verteilt unter der MIT-Lizenz. Copyright © 2026 PostMCP AI.
Available Tools
7 toolscreate_postC
Schedule or publish immediately a post to one or more social media platforms or specific accounts.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | The text body / commentary of the post. | |
| mediaUrl | No | Optional public URL of an image/video to attach. | |
| platforms | No | Target platforms for the post. | |
| scheduleDate | No | Schedule date in YYYY-MM-DD format (required if publishImmediately is false). | |
| scheduleTime | No | Schedule time in 24-hour HH:MM format (required if publishImmediately is false). | |
| targetAccounts | No | Optional specific target accounts containing platform, profileId, and userId. | |
| publishImmediately | No | If true, publishes immediately. Otherwise schedules for later. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits itself. It mentions scheduling and immediate publishing (a mutation) but does not discuss irreversibility, authentication requirements, failure handling, or what happens after publishing. This is a notable gap for a mutation 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?
The description is one concise sentence, front-loaded with the core action 'Schedule or publish immediately.' Every word contributes meaning, and there is no redundant or filler content.
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?
Despite the schema covering parameter details, the tool has no annotations or output schema, leaving the description as the only source for behavioral context. It fails to mention expected return values, error conditions, or platform-specific constraints, which is inadequate for a 7-parameter mutation 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?
All 7 parameters have schema descriptions (100% coverage), so the schema does the heavy lifting. The description adds no new semantic detail beyond the schema; it echoes the notion of platforms and accounts but does not clarify any parameter beyond what's already provided.
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 specific verbs 'Schedule or publish immediately' and identifies the resource 'a post to one or more social media platforms or specific accounts,' clearly distinguishing its dual publishing modes. However, it does not explicitly contrast with sibling tool publish_post_now, so it falls 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?
No explicit guidance is provided about when to use create_post over alternatives like publish_post_now or update_post. The description implies scheduling or immediate publishing but gives no exclusions, prerequisites, or alternative scenarios, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_postA
Cancel and delete a scheduled or failed post from the database.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The Database ObjectId of the post to delete. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavioral traits. It clearly says 'delete from the database,' which implies permanence, but it does not explicitly state irreversibility, permissions required, or potential side effects. This is a moderate gap for a destructive 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?
The description is a single, concise sentence that front-loads the action and target. There is no wasted wording or redundancy.
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 tool with one parameter and no output schema, the description fully explains what the tool does and what it operates on. It is complete for its complexity, given the sibling context and the clear 'database' reference.
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?
The schema fully documents the 'id' parameter as a Database ObjectId (100% coverage), so the description adds no extra meaning beyond the schema. The description does not elaborate on the parameter or its format, so it stays at the baseline.
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 (delete) and resource (scheduled or failed post), clearly distinguishing it from sibling tools like update_post or publish_post_now. It states exactly what the tool does and the scope of posts it affects.
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?
The phrase 'scheduled or failed post' provides clear context on when to use this tool versus alternatives, effectively excluding published posts. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_connected_accountsA
List all active, connected social media channels and their associated profile usernames.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states a read-only action ('List') without mentioning any nuances like authentication requirements, empty list behavior, or whether 'active' affects the returned data.
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?
The description is a single concise sentence that front-loads the action and resource. Every word adds value with no redundancy.
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 tool with no parameters and no output schema, the description adequately conveys the purpose and the main output elements (channels and usernames). It could be more explicit about return format, but the level is sufficient for a list operation.
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?
The tool has no parameters, and the schema is an empty object. Per the baseline for zero-parameter tools, a score of 4 is appropriate since there are no parameter semantics to clarify.
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 clearly states the tool lists active, connected social media channels and their profile usernames. The verb 'List' and specific resource 'connected social media channels' make it distinct from sibling tools like get_user_info or list_posts.
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?
The description does not provide any guidance on when to use this tool vs alternatives. No exclusions, prerequisites, or explicit context are given, so the agent must infer usage from the resource name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_user_infoA
Retrieve details of the logged-in user including subscription plan, credit balance, and AI token count.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It clearly indicates a read operation and lists the data fields returned, but it does not disclose potential errors, authentication requirements beyond 'logged-in', or whether the data is real-time. For a simple read tool, this is adequate but not rich.
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?
The description is a single sentence of 13 words, front-loading the primary action and resource. Every word adds value and there is no redundancy or filler.
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 tool with no parameters and no output schema, the description provides the core purpose and enumerates the key returned fields. It does not explain the full response structure, but the listed inclusions offer sufficient context for an agent to invoke the tool correctly.
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 are zero parameters, and the schema coverage is 100% (empty properties). Per the rubric, a baseline of 4 applies when there are no parameters. The description adds no parameter-specific details because none exist.
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 the specific verb 'Retrieve' and clearly identifies the resource as 'details of the logged-in user' with explicit mention of subscription plan, credit balance, and AI token count. This distinguishes it from sibling tools like get_connected_accounts and list_posts.
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?
The description implies this tool is for accessing current user information, but it does not explicitly state when to use it over alternatives or provide exclusions. No sibling tool comparison or when/when-not guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_postsA
Retrieve a list of scheduled, published, and failed social media posts.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. 'Retrieve' clearly indicates a read-only operation, and specifying the statuses adds context. However, it does not disclose pagination, ordering, or potential limitations, which would be expected for a list operation.
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?
The description is a single, front-loaded sentence with no filler. Every word contributes to understanding the tool's purpose and scope.
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 parameterless list tool, the description is largely sufficient. It identifies the resource and the included statuses, which is enough for an AI to decide when to use it. A minor gap is not mentioning the return format or any limits, but given the simplicity, this is acceptable.
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?
The tool has zero parameters, so there is nothing to document beyond what the schema already conveys (empty object). The description adds no parameter details, but the baseline for zero parameters is 4, and there is nothing missing.
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 ('Retrieve') and resource ('social media posts'), and further specifies the scope ('scheduled, published, and failed'). This clearly distinguishes it from sibling tools like create_post, delete_post, and publish_post_now, which are mutations.
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?
The description implies this tool is for viewing posts, contrasting with the mutating sibling tools. However, it does not explicitly state when to use this tool over alternatives like get_user_info, though the context strongly suggests it for listing posts. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
publish_post_nowA
Broadcast an existing scheduled post immediately to its platforms.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The Database ObjectId of the post to publish. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action and immediacy but does not mention potential side effects like whether the post loses its scheduled status, if the action is reversible, any permission requirements, or rate limits. This is a notable gap for a mutation 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?
The description is a single, compact sentence that immediately conveys the action, target, and timing. No filler words; every word earns its place.
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?
The description is clear at a high level but omits details such as what happens to the original scheduled post, how 'platforms' are determined (e.g., connected accounts), and any prerequisites. Given the absence of annotations and an output schema, these gaps leave the description only modestly complete.
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?
The schema provides 100% coverage for the single parameter 'id' with a clear description. The tool description adds the useful constraint that the post must be an 'existing scheduled post', which is meaningful context beyond the schema's generic 'post to publish' description.
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 the specific verb 'broadcast' and clearly identifies the resource as an 'existing scheduled post' with the immediate action of publishing to platforms. This distinguishes it from sibling tools like create_post, update_post, and delete_post, which handle different operations.
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?
The description clearly implies the use case: publishing a previously scheduled post right away. However, it does not explicitly mention alternatives or state when not to use it, though the sibling list provides no other tool for this action, making the context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_postB
Update the fields (content, platforms, schedule date/time) of an existing post.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The Database ObjectId of the post to update. | |
| status | No | Reset status of the post. | |
| content | No | Updated text body of the post. | |
| platforms | No | Updated platforms for publication. | |
| scheduleDate | No | Updated schedule date in YYYY-MM-DD format. | |
| scheduleTime | No | Updated schedule time in HH:MM format. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It simply says 'update' without explaining partial vs. full field replacement, what happens to unspecified fields, whether the status can be reset, or any side effects. For a mutation tool, this lack of nuance is a significant gap.
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?
The description is a single sentence that is front-loaded with the verb and object. Every word earns its place; there is no filler or redundancy. It is appropriately concise given the tool's straightforward nature.
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?
The tool has 6 parameters, no output schema, and no annotations, yet the description is only one short sentence. It never mentions what happens on success or failure, whether updates are partial or full, or how the status field fits into the workflow. This is insufficient for such a complex mutation tool, especially without structured metadata to fill the 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 coverage is 100%, so the baseline is 3. The description adds a high-level grouping ('schedule date/time' for scheduleDate and scheduleTime) but does not provide additional meaning beyond the parameter descriptions already present. It doesn't compensate for or extend the schema, so a 3 is appropriate.
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 clearly states the action: 'Update the fields (content, platforms, schedule date/time) of an existing post.' The verb 'update' and resource 'post' are specific, and listing the fields distinguishes it from siblings like create_post and delete_post. It omits the status field, but the core purpose is unambiguous.
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 is provided on when to use this tool versus alternatives. It doesn't mention create_post for new posts, publish_post_now for immediate publishing, or any prerequisites. The intended context is implied by the name but not explicitly stated, and no exclusions or alternative references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool targets a distinct resource or action: user info, connected accounts, and post management (list, create, publish, update, delete). The actions are clearly separated, and even create_post vs publish_post_now are distinguished by whether the post is new or existing.
All tool names follow a consistent verb_noun pattern in snake_case (get_user_info, list_posts, create_post, publish_post_now, delete_post, update_post). The naming is uniform and predictable.
Seven tools is well-scoped for a social media post management server. Each tool covers a necessary operation without redundancy or bloat, making the set easy to navigate.
The tool set provides full CRUD for posts (create, list, update, delete), plus a specialized publish action, and includes user/account context. This covers the core workflow of managing social media posts from scheduling to publication.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Draft, schedule and publish social posts to nine platforms from any AI agent.
Schedule and publish social media posts to 9 platforms from your AI agent
Draft, schedule, and publish social posts for your workspace straight from your AI.
AI-native social media publishing to LinkedIn, Instagram, Threads, TikTok, and X.
Related MCP Servers
- AlicenseBqualityCmaintenanceConnects to multiple social media platforms (Twitter/X, Mastodon, LinkedIn), allowing users to create and publish content across platforms through natural language instructions.31422MIT
- AlicenseAqualityAmaintenanceEnables AI assistants to schedule and publish social media posts to platforms like Instagram, TikTok, YouTube, LinkedIn, Facebook, X, Threads, and Pinterest using natural language.332783MIT
- AlicenseAqualityDmaintenanceEnables AI assistants to manage social media accounts and CRM operations, including posting, analytics, inbox management, and customer management.22Apache 2.0
- FlicenseNot gradedqualityCmaintenanceEnables AI agents to create, schedule, and manage social media posts across 10 platforms via a unified API.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/postmcp/postmcp-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server