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    Reddit Mcp

    Model Context Protocol server implementation for Reddit Python-based implementation.

    219 stars
    Python
    Updated Nov 3, 2025
    mcp
    mcp-server
    reddit
    reddit-api

    Table of Contents

    • What is MCP?
    • Features
    • Installation
    • Available Tools
    • Read-only Tools (require only client credentials):
    • Authenticated Tools (require user credentials):
    • Example Queries
    • Advanced Features
    • AI-Driven Analysis
    • Smart Response Formatting
    • Authentication
    • Contributing
    • License

    Table of Contents

    • What is MCP?
    • Features
    • Installation
    • Available Tools
    • Read-only Tools (require only client credentials):
    • Authenticated Tools (require user credentials):
    • Example Queries
    • Advanced Features
    • AI-Driven Analysis
    • Smart Response Formatting
    • Authentication
    • Contributing
    • License

    Documentation

    Reddit MCP Server

    This repository contains a Model Context Protocol server implementation for Reddit that allows AI assistants to access and interact with Reddit content through PRAW (Python Reddit API Wrapper).

    image

    What is MCP?

    The Model Context Protocol (MCP) is a standard for enabling AI assistants to interface with external services, tools, and data sources. This server implements the MCP specification to provide access to Reddit content.

    To know more about MCP, Check this video

    Features

    • Get detailed user information with engagement analysis
    • Retrieve user comment and post history with flexible filtering
    • Fetch and analyze top posts from any subreddit
    • Search for posts across all of Reddit or within specific subreddits using search terms
    • Get comprehensive subreddit statistics and health metrics
    • View trending subreddits with growth patterns
    • Create strategic posts with timing recommendations
    • Reply to posts and comments with engagement optimization
    • AI-driven insights and recommendations
    • Smart response formatting with engagement metrics

    Installation

    1. Clone this repository

    bash
    git clone https://github.com/Arindam200/reddit-mcp.git
    cd reddit-mcp

    2. Connect to the MCP server

    Copy the below json with the appropriate {{PATH}} values:

    json
    {
         "mcpServers": {
           "reddit": {
             "command": "{{PATH_TO_UV}}", // Run `which uv` and place the output here
             "args": [
               "--directory",
               "{{PATH_TO_SRC}}", // cd into the repo, run `pwd` and enter the output here
               "run",
               "server.py"
             ],
             "env": {
               "REDDIT_CLIENT_ID": "your_client_id",
               "REDDIT_CLIENT_SECRET": "your_client_secret",
               "REDDIT_USERNAME": "your_username", // Optional for authenticated operations
               "REDDIT_PASSWORD": "your_password" // Optional for authenticated operations
             }
           }
         }
       }

    You can obtain Reddit API credentials by creating an app at Reddit's app preferences page.

    For Claude, save this as claude_desktop_config.json in your Claude Desktop configuration directory at:

    code
    ~/Library/Application Support/Claude/claude_desktop_config.json

    For Cursor, save this as mcp.json in your Cursor configuration directory at:

    code
    ~/.cursor/mcp.json

    3. Restart Claude Desktop / Cursor

    Open Claude Desktop and you should now see Reddit as an available integration.

    Or restart Cursor.

    Available Tools

    The server provides the following tools:

    Read-only Tools (require only client credentials):

    • get_user_info(username) - Get detailed user analysis with engagement insights
    • get_user_comments(username, sort, time_filter, limit) - Get a user's comment history with filtering options
    • get_user_posts(username, sort, time_filter, limit) - Get a user's post/submission history with filtering options
    • get_top_posts(subreddit, time_filter, limit) - Get and analyze top posts
    • search_posts(query, subreddit, sort, time_filter, limit) - Search for posts across Reddit or within a specific subreddit
    • get_subreddit_stats(subreddit) - Get comprehensive subreddit analysis
    • get_trending_subreddits() - Get list of trending subreddits
    • get_submission_by_url(url) - Get a Reddit submission by its URL
    • get_submission_by_id(submission_id) - Get a Reddit submission by its ID

    Authenticated Tools (require user credentials):

    • who_am_i() - Get information about the currently authenticated user
    • create_post(subreddit, title, content, flair, is_self) - Create an optimized post
    • reply_to_post(post_id, content, subreddit) - Add a reply with engagement insights
    • reply_to_comment(comment_id, content, subreddit) - Add a strategic reply

    Example Queries

    Here are some examples of what you can ask an AI assistant connected to this server:

    • "Who am I on Reddit?" or "Show my Reddit profile"
    • "Analyze u/spez's Reddit activity"
    • "Show me u/spez's recent comments"
    • "Get the top posts by u/poem_for_your_sprog from the past year"
    • "Show me the most controversial comments by u/username"
    • "Show me the top posts from r/Python this week"
    • "Search for posts about 'machine learning' across all of Reddit"
    • "Find posts about 'beginner tutorials' in r/learnprogramming from this month"
    • "Get statistics about r/AskReddit"
    • "What are the trending subreddits right now?"
    • "Create a post in r/Python about a new project"
    • "Reply to this post with an insightful comment"
    • "What's the best time to post in this subreddit?"

    Advanced Features

    AI-Driven Analysis

    The server provides intelligent analysis in several areas:

    1. User Analysis

    • Engagement patterns
    • Activity trends
    • Community influence
    • Personalized recommendations

    2. Post Analysis

    • Performance metrics
    • Engagement quality
    • Timing optimization
    • Content impact assessment

    3. Community Analysis

    • Health indicators
    • Growth patterns
    • Activity metrics
    • Engagement opportunities

    Smart Response Formatting

    • Organized bullet points
    • Engagement statistics
    • AI-driven insights
    • Strategic recommendations
    • Performance metrics

    Authentication

    The server supports two levels of authentication:

    1. Read-only Access

    • Requires: client_id and client_secret
    • Allows: Fetching public data, reading posts/comments

    2. Authenticated Access

    • Requires: All read-only credentials PLUS username and password
    • Allows: All read-only operations PLUS posting and commenting

    Contributing

    Contributions are welcome! Please feel free to submit a Pull Request.

    License

    This project is licensed under the MIT License - see the LICENSE file for details.

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