What can you do with this server?

The crosspost-mcp server enables AI agents to cross-post content to multiple social media platforms using free APIs. * Post to Telegram (post_to_telegram): Send a message (up to 4,096 characters) to a configured Telegram channel, with support for HTML formatting ( , , , ). * Post to Discord (post_to_discord): Send a message (up to 2,000 characters) to a configured Discord channel via webhook, with support for Discord markdown (**bold**, *italic*, `code`, ```block```). * Cross-post to all platforms simultaneously (post_to_all): Broadcast the same message to all configured platforms in parallel. Failures on one platform don't affect others — each result is reported separately with an overall status of ok, partial, or error. * Extensible architecture: Mastodon, Bluesky, and Reddit are planned for future versions. New platforms can be added by dropping a module in the platforms/ folder. * Secure configuration: Platform credentials are managed via environment variables or a .env file.

Which integrations are available for this server?

Allows posting content to Bluesky via App Password authentication (planned for v0.3.0). Allows posting messages to a Discord channel via webhooks. Allows posting content to a Mastodon instance (planned for v0.2.0). Allows posting content to Reddit via OAuth (planned for v0.4.0). Allows posting messages to a Telegram channel via Bot API.

How do I use crosspost-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@crosspost-mcp Cross-post to all: New blog post is up!" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

crosspost-mcp

by Aleksey-Panf

Overview Schema Related Servers Score Discussions

Python

Remote

crosspost-mcp

Glama score

MCP server that lets AI agents cross-post content to Telegram, Discord, Mastodon, Bluesky, and Reddit — using free APIs only.

Python 3.11+ License: MIT MCP FastMCP

Why crosspost-mcp

AI agents can now draft, research, and refine content end-to-end — but publishing to social media is still the manual bottleneck. crosspost-mcp closes that gap by exposing posting tools over the Model Context Protocol, so Claude Desktop, Cursor, and other MCP-compatible clients can publish on your behalf with a single prompt.

Related MCP server: Outpost

Demo

Claude calls post_to_discord and the message appears in your channel instantly:

Demo

Features

Free APIs only — no paid SaaS middlemen; Telegram Bot API, Discord webhooks, and upcoming platform APIs are all free-tier friendly
Async parallel posting — post_to_all fans out to every configured platform concurrently
Type-hinted — full Python type annotations on tools and platform modules
Dataclass configs — frozen dataclasses per platform with clear missing-variable errors
Easy to extend — add a new platform by dropping a module in platforms/ and registering a tool

Supported Platforms

Platform	Status	Free Tier	Notes
Telegram	✅ v0.1.0	unlimited	Bot API
Discord	✅ v0.1.0	unlimited	webhooks
Mastodon	🚧 v0.2.0	unlimited	requires instance
Bluesky	🚧 v0.3.0	unlimited	App Password
Reddit	🚧 v0.4.0	rate-limited	OAuth

🚀 Quick Start

Clone & install

git clone https://github.com/Aleksey-Panf/crosspost-mcp.git
cd crosspost-mcp
pip install -e .

Setup credentials

Copy the example env file and fill in your tokens:

cp .env.example .env

Edit .env with your Telegram bot token, Discord webhook URL, and any other platform credentials you plan to use.

Add to Claude Desktop

Open your Claude Desktop MCP config:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the server entry (adjust the path to your clone):

{
  "mcpServers": {
    "crosspost-mcp": {
      "command": "crosspost-mcp",
      "cwd": "/path/to/crosspost-mcp",
      "env": {
        "TELEGRAM_BOT_TOKEN": "your_bot_token",
        "TELEGRAM_CHAT_ID": "your_chat_id",
        "DISCORD_WEBHOOK_URL": "https://discord.com/api/webhooks/..."
      }
    }
  }
}

Tip: If crosspost-mcp is not on your PATH, use the full path to the executable inside your virtualenv, or point command to python with args: ["-m", "crosspost_mcp.server"].

Cursor users can add the same block under Settings → MCP → Add server.

Restart Claude Desktop

Fully quit and relaunch Claude Desktop (or reload MCP in Cursor). The post_to_telegram, post_to_discord, and post_to_all tools should appear in the tool list.

Usage Examples

Give your AI agent natural-language instructions — it picks the right MCP tool automatically.

Example 1 — Discord only

Post to Discord: "v0.1.0 is live — crosspost-mcp now supports Telegram and Discord webhooks."

Claude calls post_to_discord with the message text and returns the Discord message_id and channel_id.

Example 2 — Telegram only

Announce on Telegram that we shipped parallel cross-posting. Use bold for the version number.

Claude calls post_to_telegram with HTML formatting (<b>v0.1.0</b>) and confirms the message_id.

Example 3 — Cross-post everywhere

Cross-post this to all platforms: "New blog post is up — link in bio."

Claude calls post_to_all, which posts to Telegram and Discord in parallel and returns a combined status (ok, partial, or error) with per-platform results.

🔧 Tool Reference

`post_to_telegram`

Post a message to the configured Telegram channel.


Signature	`post_to_telegram(text: str) -> dict`
Arguments	`text` — message body (max 4,096 chars). Supports HTML: `<b>`, `<i>`, `<code>`, `<a href="">`
Returns	Platform result dict

Example response:

{
  "platform": "telegram",
  "status": "ok",
  "message_id": 42,
  "chat_id": -1001234567890
}

`post_to_discord`

Post a message to the configured Discord channel via webhook.


Signature	`post_to_discord(text: str) -> dict`
Arguments	`text` — message content (max 2,000 chars). Supports Discord markdown: `bold`, `italic`, `code`, ```block```
Returns	Platform result dict

Example response:

{
  "platform": "discord",
  "status": "ok",
  "message_id": "1234567890123456789",
  "channel_id": "9876543210987654321"
}

`post_to_all`

Cross-post the same message to all configured platforms in parallel.


Signature	`post_to_all(text: str) -> dict`
Arguments	`text` — message text. Platforms enforce their own length limits independently
Returns	Aggregated result with overall status and per-platform entries

Individual platform failures do not abort the others. Each failure is reported with status: "error" and an error message.

Example response:

{
  "status": "ok",
  "results": [
    {
      "platform": "telegram",
      "status": "ok",
      "message_id": 42,
      "chat_id": -1001234567890
    },
    {
      "platform": "discord",
      "status": "ok",
      "message_id": "1234567890123456789",
      "channel_id": "9876543210987654321"
    }
  ]
}

Getting Credentials

Open Telegram and message @BotFather.
Send /newbot, follow the prompts, and copy the bot token.
Add the bot as an admin to your target channel with Post Messages permission.
Get the chat ID:
- For public channels, use @channelname (include the @).
- For private channels, forward a channel message to @userinfobot or call getUpdates on the Bot API after posting in the channel.
Set TELEGRAM_BOT_TOKEN and TELEGRAM_CHAT_ID in your .env.

Discord

Open your Discord server and go to the target channel.
Click the gear icon → Integrations → Webhooks → New Webhook.
Name the webhook, select the channel, and click Copy Webhook URL.
Set DISCORD_WEBHOOK_URL in your .env.

No bot application or OAuth flow required — webhooks are the simplest path for AI agent posting.

Project Structure

crosspost-mcp/
├── assets/                          # Screenshots and demo images
├── src/
│   └── crosspost_mcp/
│       ├── __init__.py
│       ├── config.py                # Dataclass configs loaded from .env
│       ├── server.py                # FastMCP server and tool definitions
│       └── platforms/
│           ├── __init__.py
│           ├── telegram.py          # Telegram Bot API client
│           └── discord.py           # Discord webhook client
├── tests/
├── .env.example                     # Credential template
├── pyproject.toml
└── README.md

Roadmap

Telegram support
Discord support
Parallel cross-posting
Mastodon support (v0.2.0)
Bluesky support (v0.3.0)
Reddit support (v0.4.0)
Media/image attachments
Scheduled posting

Contributing

Contributions are welcome — bug reports, platform modules, and documentation improvements all help. Open an issue to discuss larger changes before submitting a pull request.

Custom MCP Development

I build production-ready MCP servers on demand for custom platforms and workflows.

Delivery: 3–7 days
Workflow: Async-only, no calls
Payment: USDT
Contact: Telegram @AlexAi14 or open a GitHub issue

License

MIT — see LICENSE for details.

Topics: mcp · model-context-protocol · fastmcp · telegram-bot · discord-webhook · ai-agents · claude · llm-tools

Available Tools

3 tools

post_to_allA

Post the same message to all configured platforms concurrently.

Runs all platform posts in parallel. Individual platform failures do not abort other platforms; each result is reported separately.

ParametersJSON Schema

Name	Required	Description	Default
`text`	Yes	Message text. Note that platforms have different length limits (Discord 2000, Telegram 4096). Text exceeding a platform's limit will fail for that platform only.

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations, the description fully carries the burden. It discloses concurrency, failure isolation, separate result reporting, and platform-specific length limits in the parameter description, offering complete behavioral transparency.

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?

The description is concise with two front-loaded sentences and an additional paragraph for behavior. Every sentence adds value, with no fluff or repetition.

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

Completeness5/5

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

Given the tool's simplicity (1 param, output schema exists), the description covers concurrency, failure handling, and parameter constraints. It is complete for an AI agent to understand usage and behavior.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already provides parameter details including length limits. The description adds no new semantic value beyond the schema, thus baseline 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool posts the same message to all configured platforms concurrently. It uses specific verb 'Post', resource 'message', and target 'all configured platforms', distinguishing it from siblings post_to_discord and post_to_telegram.

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

Usage Guidelines4/5

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

The description explains that posts run in parallel and individual failures do not abort others, providing clear context. However, it does not explicitly state when to avoid this tool or compare to alternatives, missing some guidance.

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

post_to_discordC

Post a message to the configured Discord channel via webhook.

ParametersJSON Schema

Name	Required	Description	Default
`text`	Yes	Message content (max 2000 chars). Supports Discord markdown: bold, italic, `code`, ```block```.

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions 'via webhook,' hinting at configuration dependency, but fails to mention other important behaviors like rate limits, success/failure feedback, or mutation visibility.

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?

Single sentence with no redundancy. However, it could be expanded slightly to improve clarity without becoming verbose. No structural issues, but slightly under-informative.

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?

Given the tool's simplicity (1 parameter, output schema present), the description is minimally adequate. It identifies the platform and method, but lacks guidance on configuration scope or integration with sibling tools, leaving gaps for a new user.

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%, with the text parameter already specifying max length and markdown support. The tool description adds no new parameter insight beyond what the schema provides, meeting the baseline for full coverage.

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

Purpose4/5

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

The description clearly states the action (post a message) and the specific resource (Discord channel via webhook). It distinguishes from siblings like post_to_telegram by platform, but does not explicitly differentiate from post_to_all, leaving some ambiguity.

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 explicit guidance on when to use this tool vs siblings. The description provides no context about prerequisites, alternatives, or scenarios, relying entirely on sibling names for differentiation.

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

post_to_telegramB

Post a message to the configured Telegram channel.

ParametersJSON Schema

Name	Required	Description	Default
`text`	Yes	Message text (max 4096 chars). Supports HTML formatting: <b>bold</b>, <i>italic</i>, <code>mono</code>, <a href="">link</a>.

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description must compensate. It only says 'configured' without explaining configuration, error handling, or rate limits. Minimal behavioral disclosure.

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?

Single sentence, no waste. Front-loaded with action and target.

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-parameter tool with an output schema, the description is adequate but could mention that an output schema exists or common failure modes.

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 coverage is 100% and the schema describes the parameter well, but the tool description itself adds no meaning beyond 'post a message'. No mention of the 4096 char limit or HTML formatting, which are in the schema but not reinforced.

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

Purpose5/5

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

The description clearly states the verb (post) and resource (Telegram channel). It explicitly distinguishes from siblings 'post_to_all' and 'post_to_discord' by targeting Telegram specifically.

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?

No explicit guidance on when to use this tool versus 'post_to_all' or 'post_to_discord'. Usage is implied but not contrasted.

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

Install Server

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

TDQS

A3.8/5.0

Disambiguation5/5

Each tool has a distinct purpose: posting to all platforms, or to a specific platform. There is no overlap or ambiguity.

Naming Consistency5/5

All tool names follow the consistent 'post_to_<platform>' pattern in snake_case, making them predictable.

Tool Count5/5

Three tools is appropriate for a cross-posting service—covering both all-in-one and specific platform posting without unnecessary bloat.

Completeness5/5

The tool set covers the full cross-posting workflow: posting to all configured platforms, and individually to Discord and Telegram. No obvious gaps.

Maintenance

ActivityStale

ResponsivenessSyncing

Resources

GitHub Repository

Need Help?

Related Servers

Unclaimed servers have limited discoverability.

Looking for Admin?

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

Related MCP Connectors

qpost-mcp
io.github.arslan2012
MCP server for QPost — lets AI agents publish video and image posts to YouTube, TikTok, Instagram.
Social Media
1
UnifAPI
com.unifapi
Hosted MCP server for live public-data APIs and Skills for AI agents.
Open Data Search AI & Machine Learning
2
mcp-server A
cc.thecolony
Remote MCP server for The Colony — a social network for AI agents (posts, DMs, search, marketplace).
Knowledge & Memory Research & Data
21623
socialclaw B
io.github.ndesv21
Connect any AI agent to 11+ social platforms: schedule, publish & track posts via hosted MCP.
Social Media Marketing
32282

Related MCP Servers

Social CLI MCP
Social Media Communication
alessio-web-dev
A
license
Not graded
quality
D
maintenance
MCP server for posting to Twitter/X, Reddit, LinkedIn, Instagram, and email via CLI or AI agents, with Telegram bot control and security confirmations.
Updated 5 months ago (2026-04-03 09:50 UTC)
7
MIT
Outpost
Social Media App Automation
andrezani
A
license
Not graded
quality
C
maintenance
Social media API and MCP server for AI agents that enables publishing to X, Instagram, LinkedIn, Reddit, Bluesky, and Threads from a single endpoint.
Updated 3 months ago (2026-06-05 19:39 UTC)
1
MIT
postlayer-connect
Social Media Communication
pokakrisztian2
A
license
A
quality
C
maintenance
A local MCP server that enables AI assistants to post to social media platforms (LinkedIn, X, Bluesky, Mastodon, Reddit, etc.) using your own app credentials, with encrypted token storage and no middleman.
Updated 2 months ago (2026-07-04 17:52 UTC)
5
MIT
postbolt-mcp
Social Media Communication
Whitemarmot
A
license
Not graded
quality
D
maintenance
MCP server that enables AI agents to schedule and publish posts to 13+ social platforms via PostBolt's API with zero code.
Updated 6 months ago (2026-03-03 18:10 UTC)
54
MIT

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/Aleksey-Panf/crosspost-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server