macrocosm-os/macrocosmos-mcp

CategoryDatabase
AuthorCommunity
Stars464
PricingFree

Overview

The macrocosmos-mcp tool bridges the gap between static LLM knowledge and live social discourse by providing a standardized interface for X, Reddit, and YouTube data. Instead of building custom scrapers or managing multiple API authentications, developers can use this MCP server to pull real-time posts, user activity, and thread discussions directly into their model's context. It supports granular filtering by search phrases and date ranges, making it particularly useful for sentiment analysis, trend tracking, and competitive intelligence. By decoupling the data fetching logic from the application layer, it allows for seamless integration into any MCP-compliant client, transforming an LLM from a general reasoner into a real-time social monitor.

Highlights

  • Unified access to X, Reddit, and YouTube data
  • Real-time filtering by keywords, users, and dates
  • Eliminates need for custom social media scrapers
  • Standardized MCP integration for rapid deployment
  • Ideal for live sentiment and trend analysis

Full Documentation

Macrocosmos MCP

<p align="center">
Official Macrocosmos <a href="https://github.com/modelcontextprotocol">Model Context Protocol (MCP)</a> server that enables interaction with X (Twitter) and Reddit, powered by Data Universe (SN13) on Bittensor. This server allows MCP clients like <a href="https://www.anthropic.com/claude">Claude Desktop</a>, <a href="https://www.cursor.so">Cursor</a>, <a href="https://codeium.com/windsurf">Windsurf</a>, <a href="https://github.com/openai/openai-agents-python">OpenAI Agents</a> and others to fetch real-time social media data.
</p>

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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:

json
{
  "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:
| Parameter | Type | Description |
|-----------|------|-------------|
| source | string | REQUIRED. Platform: 'X' or 'REDDIT' (case-sensitive) |
| usernames | list | Up to 5 usernames. For X: @ is optional. Not available for Reddit |
| keywords | list | Up to 5 keywords. For Reddit: first item is subreddit (e.g., 'r/MachineLearning') |
| start_date | string | ISO format (e.g., '2024-01-01T00:00:00Z'). Defaults to 24h ago |
| end_date | string | ISO format. Defaults to now |
| limit | int | Max results 1-1000. Default: 10 |
| keyword_mode | string | '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:
| Parameter | Type | Description |
|-----------|------|-------------|
| tasks | list | REQUIRED. List of task objects (see below) |
| name | string | Optional name for the task |
| email | string | Email for notification when complete |

Task object structure:

json
{
"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:
| Parameter | Type | Description |
|-----------|------|-------------|
| gravity_task_id | string | REQUIRED. The task ID from create_gravity_task |
| include_crawlers | bool | Include 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:
| Parameter | Type | Description |
|-----------|------|-------------|
| crawler_id | string | REQUIRED. Get from get_gravity_task_status |
| max_rows | int | Max rows to include. Default: 10000 |
| email | string | Email 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:
| Parameter | Type | Description |
|-----------|------|-------------|
| dataset_id | string | REQUIRED. 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:
| Parameter | Type | Description |
|-----------|------|-------------|
| gravity_task_id | string | REQUIRED. The task ID to cancel |

---

7. cancel_dataset - Cancel Build or Purge Dataset

Cancel a dataset build or purge a completed dataset.

Parameters:
| Parameter | Type | Description |
|-----------|------|-------------|
| dataset_id | string | REQUIRED. The dataset ID to cancel/purge |

---

Example Workflows

Quick Query (On-Demand)

code
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)

code
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

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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"

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MIT License
Made with love by the Macrocosmos team

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