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MCP Server

macrocosmos-mcp

A Python-based MCP server that provides access to X (Twitter), Reddit, and Hugging Face data through the SN13 and SN1 APIs.

27
GitHub Stars
3/10/2026
Last Updated
MCP Server Configuration
1{
2 "name": "macrocosmos",
3 "command": "uvx",
4 "args": [
5 "macrocosmos-mcp"
6 ],
7 "env": {
8 "MC_API": ""
9 }
10}
JSON10 lines
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README Documentation

Macrocosmos MCP

Official Macrocosmos Model Context Protocol (MCP) server that enables interaction with X (Twitter) and Reddit, powered by Data Universe (SN13) on Bittensor. This server allows MCP clients like Claude Desktop, Cursor, Windsurf, OpenAI Agents and others to fetch real-time social media data.


Quickstart with Claude Desktop

  1. Get your API key from Macrocosmos. There is a free tier with $5 of credits to start.
  2. Install uv (Python package manager), install with curl -LsSf https://astral.sh/uv/install.sh | sh or see the uv repo for additional install methods.
  3. Go to Claude > Settings > Developer > Edit Config > claude_desktop_config.json to include the following:
{
  "mcpServers": {
    "macrocosmos": {
      "command": "uvx",
      "args": ["macrocosmos-mcp"],
      "env": {
        "MC_API": "<insert-your-api-key-here>"
      }
    }
  }
}

Available Tools

1. query_on_demand_data - Real-time Social Media Queries

Fetch real-time data from X (Twitter) and Reddit. Best for quick queries up to 1000 results.

Parameters:

ParameterTypeDescription
sourcestringREQUIRED. Platform: 'X' or 'REDDIT' (case-sensitive)
usernameslistUp to 5 usernames. For X: @ is optional. Not available for Reddit
keywordslistUp to 5 keywords. For Reddit: first item is subreddit (e.g., 'r/MachineLearning')
start_datestringISO format (e.g., '2024-01-01T00:00:00Z'). Defaults to 24h ago
end_datestringISO format. Defaults to now
limitintMax results 1-1000. Default: 10
keyword_modestring'any' (default) or 'all'

Example prompts:

  • "What has @elonmusk been posting about today?"
  • "Get me the latest posts from r/bittensor about dTAO"
  • "Fetch 50 tweets about #AI from the last week"

2. create_gravity_task - Large-Scale Data Collection

Create a Gravity task for collecting large datasets over 7 days. Use this when you need more than 1000 results.

Parameters:

ParameterTypeDescription
taskslistREQUIRED. List of task objects (see below)
namestringOptional name for the task
emailstringEmail for notification when complete

Task object structure:

{
  "platform": "x",           // 'x' or 'reddit'
  "topic": "#Bittensor",     // For X: MUST start with '#' or '$'
  "keyword": "dTAO"          // Optional: filter within topic
}

Important: For X (Twitter), topics MUST start with # or $ (e.g., #ai, $BTC). Plain keywords are rejected.

Example prompts:

  • "Create a gravity task to collect #Bittensor tweets for the next 7 days"
  • "Start collecting data from r/MachineLearning about neural networks"

3. get_gravity_task_status - Check Collection Progress

Monitor your Gravity task and see how much data has been collected.

Parameters:

ParameterTypeDescription
gravity_task_idstringREQUIRED. The task ID from create_gravity_task
include_crawlersboolInclude detailed stats. Default: True

Returns: Task status, crawler IDs, records_collected, bytes_collected

Example prompts:

  • "Check the status of my Bittensor data collection task"
  • "How many records have been collected so far?"

4. build_dataset - Build & Download Dataset

Build a dataset from collected data before the 7-day completion.

Warning: This will STOP the crawler and de-register it from the network.

Parameters:

ParameterTypeDescription
crawler_idstringREQUIRED. Get from get_gravity_task_status
max_rowsintMax rows to include. Default: 10000
emailstringEmail for notification when ready

Example prompts:

  • "Build a dataset from my Bittensor crawler with 5000 rows"
  • "I have enough data, build the dataset now"

5. get_dataset_status - Check Build Progress & Download

Check dataset build progress and get download links when ready.

Parameters:

ParameterTypeDescription
dataset_idstringREQUIRED. The dataset ID from build_dataset

Returns: Build status (10 steps), and when complete: download URLs for Parquet files

Example prompts:

  • "Is my dataset ready to download?"
  • "Get the download link for my Bittensor dataset"

6. cancel_gravity_task - Stop Data Collection

Cancel a running Gravity task.

Parameters:

ParameterTypeDescription
gravity_task_idstringREQUIRED. The task ID to cancel

7. cancel_dataset - Cancel Build or Purge Dataset

Cancel a dataset build or purge a completed dataset.

Parameters:

ParameterTypeDescription
dataset_idstringREQUIRED. The dataset ID to cancel/purge

Example Workflows

Quick Query (On-Demand)

User: "What's the sentiment about $TAO on Twitter today?"
→ Uses query_on_demand_data to fetch recent tweets
→ Returns up to 1000 results instantly

Large Dataset Collection (Gravity)

User: "I need to collect a week's worth of #AI tweets for analysis"

1. create_gravity_task → Returns gravity_task_id
2. get_gravity_task_status → Monitor progress, get crawler_ids
3. build_dataset → When ready, build the dataset
4. get_dataset_status → Get download URL for Parquet file

Example Prompts

On-Demand Queries

  • "What has the president of the U.S. been saying over the past week on X?"
  • "Fetch me information about what people are posting on r/politics today."
  • "Please analyze posts from @elonmusk for the last week."
  • "Get me 100 tweets about #Bittensor and analyze the sentiment"

Large-Scale Collection

  • "Create a gravity task to collect data about #AI from Twitter and r/MachineLearning from Reddit"
  • "Start a 7-day collection of $BTC tweets with keyword 'ETF'"
  • "Check how many records my gravity task has collected"
  • "Build a dataset with 10,000 rows from my crawler"

MIT License Made with love by the Macrocosmos team

Quick Install

Quick Actions

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Key Features

Model Context Protocol
Secure Communication
Real-time Updates
Open Source

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