Facebook Pages Manager MCP server for AI agents

This project is a MCP server for automating and managing interactions on a Facebook Page using the Facebook Graph API. It provides tools to create posts, moderate comments, fetch post insights, and filter negative feedback that can be used with Claude or other LLM-based agents.

Installation

Prerequisites

To use this Facebook MCP server, you'll need:

Python installed on your system
Facebook Page credentials (access token and page ID)

Step 1: Clone the Repository

git clone https://github.com/your-org/facebook-mcp-server.git
cd facebook-mcp-server

Step 2: Install Dependencies

Install dependencies using uv, a fast Python package manager:

# Install uv if you don't have it already
curl -Ls https://astral.sh/uv/install.sh | bash

# Install project dependencies
uv pip install -r requirements.txt

Step 3: Configure Environment Variables

Create a .env file in the root directory with your Facebook credentials:

FACEBOOK_ACCESS_TOKEN=your_facebook_page_access_token
FACEBOOK_PAGE_ID=your_page_id

You can obtain these credentials from the Facebook Developer platform at Facebook Graph API Explorer.

Integration with Claude Desktop

Configuration

To integrate the Facebook MCP server with Claude Desktop:

Open Claude Desktop
Navigate to Settings → Developer → Edit Config
Add the following entry to the configuration file:

"FacebookMCP": {
  "command": "uv",
  "args": [
    "run",
    "--with",
    "mcp[cli]",
    "--with",
    "requests",
    "mcp",
    "run",
    "/path/to/facebook-mcp-server/server.py"
  ]
}

Be sure to replace /path/to/facebook-mcp-server/ with the actual path where you cloned the repository.

Available Tools

The Facebook MCP server provides the following tools:

Content Creation

post_to_facebook - Create a new Facebook post with a message
post_image_to_facebook - Post an image with a caption
update_post - Update an existing post's message
schedule_post - Schedule a post for future publication
delete_post - Delete a specific post by ID

Comment Management

reply_to_comment - Reply to a specific comment on a post
delete_comment / delete_comment_from_post - Delete a specific comment by ID
hide_comment - Hide a comment from public view
unhide_comment - Unhide a previously hidden comment
filter_negative_comments - Filter out comments with negative sentiment keywords
bulk_delete_comments - Delete multiple comments by ID
bulk_hide_comments - Hide multiple comments by ID

Analytics and Insights

get_page_posts - Retrieve recent posts from the Page
get_post_comments - Fetch comments on a given post
get_number_of_comments - Count comments on a post
get_number_of_likes - Count likes on a post
get_post_impressions - Get total impressions on a post
get_post_impressions_unique - Get number of unique users who saw the post
get_post_impressions_paid - Get number of paid impressions
get_post_impressions_organic - Get number of organic impressions
get_post_engaged_users - Get number of users who engaged with the post
get_post_clicks - Get number of clicks on the post
get_post_reactions_like_total - Get total number of 'Like' reactions
get_post_reactions_breakdown - Get all reaction counts in one call
get_post_top_commenters - Get the top commenters on a post
get_page_fan_count - Retrieve the total number of Page fans
get_post_share_count - Get the number of shares on a post

User Interaction

send_dm_to_user - Send a direct message to a user

Usage Examples

Creating a Post

To create a new post on your Facebook Page:

response = post_to_facebook("Check out our latest product announcement!")
post_id = response["id"]
print(f"Created post with ID: {post_id}")

Moderating Comments

To fetch and hide negative comments:

# Get comments from a post
comments = get_post_comments(post_id)

# Filter negative comments
negative_comments = filter_negative_comments(comments)

# Hide negative comments
for comment in negative_comments:
    hide_comment(comment["id"])

Analyzing Post Performance

To get insights about a post's performance:

# Get post engagement metrics
impressions = get_post_impressions(post_id)
engaged_users = get_post_engaged_users(post_id)
likes = get_number_of_likes(post_id)
comments = get_number_of_comments(post_id)
shares = get_post_share_count(post_id)

print(f"Post performance: {impressions} impressions, {engaged_users} engaged users")
print(f"Engagement: {likes} likes, {comments} comments, {shares} shares")

Scheduling Content

To schedule a post for future publication:

# Schedule a post for tomorrow at 10 AM
import datetime
tomorrow = datetime.datetime.now() + datetime.timedelta(days=1)
scheduled_time = tomorrow.replace(hour=10, minute=0, second=0).isoformat()

response = schedule_post("Our weekend special starts tomorrow!", scheduled_time)
scheduled_post_id = response["id"]

How to install this MCP server

For Claude Code

To add this MCP server to Claude Code, run this command in your terminal:

claude mcp add-json "facebook-mcp-server" '{"command":"uv","args":["run","--with","mcp[cli]","--with","requests","mcp","run","/path/to/facebook-mcp-server/server.py"]}'

See the official Claude Code MCP documentation for more details.

For Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "facebook-mcp-server": {
            "command": "uv",
            "args": [
                "run",
                "--with",
                "mcp[cli]",
                "--with",
                "requests",
                "mcp",
                "run",
                "/path/to/facebook-mcp-server/server.py"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.

For Claude Desktop

To add this MCP server to Claude Desktop:

1. Find your configuration file:

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

2. Add this to your configuration file:

{
    "mcpServers": {
        "facebook-mcp-server": {
            "command": "uv",
            "args": [
                "run",
                "--with",
                "mcp[cli]",
                "--with",
                "requests",
                "mcp",
                "run",
                "/path/to/facebook-mcp-server/server.py"
            ]
        }
    }
}

3. Restart Claude Desktop for the changes to take effect