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MCP server · Developer Tools

macrocosm-os/macrocosmos-mcp

The MCP for macrocosmos subnets.

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Scored 5 days ago · breakdown

About macrocosm-os/macrocosmos-mcp

macrocosm-os/macrocosmos-mcp is an MCP server published by macrocosm-os in the Developer Tools category: the MCP for macrocosmos subnets.

The repository has 29 stars and 7 forks, with the last commit 2 months ago. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/macrocosm-os/macrocosmos-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository 7 days ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • !License declaredNo license file. Legally you have no right to use it in a product.
  • !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
  • !Dependencies pinnedNo lockfile. Installs can pull different code over time.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v0.2.2v0.2.2 — Fix broken install (pin mcp SDK <2) · 20 Aug 2026Fixed Broken install on fresh environments (#13): MCP SDK 2.0.0 removed `mcp.server.fastmcp`, and the unpinned `mcp[cli]` dependency made every new `uvx macrocosmos-mcp` / `pip install macrocosmos-mcp` crash at import with…
v0.2.1Add Gravity data collection for mcp. · 9 Jan 2026⏺ Summary Adds Gravity API tools for large-scale data collection to the Macrocosmos MCP server. This enables users to collect unlimited social media data over 7 days, compared to the existing on-demand queries which are limited to 1000…
v1.0.0SSE server · 2 Jul 2025SSE server that are available on https://bittensor.mcp.macrocosmos.ai/sse. Can be used only with MacroCosmos keys

README

Macrocosmos MCP


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:

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:

{
  "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)

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

README fetched from the repository 7 days ago. The original is authoritative.

Questions

About macrocosm-os/macrocosmos-mcp

How do I install macrocosm-os/macrocosmos-mcp?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is macrocosm-os/macrocosmos-mcp safe to use with an AI agent?

Its trust score is 50 out of 100 (fair). It passes 2 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is macrocosm-os/macrocosmos-mcp still maintained?

Yes — the latest release is v0.2.2 (20 Aug 2026), and the last commit was 2 months ago. The repository has 29 stars.