Massive Context MCP Server

by egoughnour Your server? Claim it

local only

Massive Context MCP runs on your own machine — the client starts it, so there is no endpoint to ping. 86 installs a week from pypi. Last commit 19 Jan 2026.

Handles 10M+ token contexts with chunking, sub-queries, and local Ollama inference.

Installs per day peak 70 · avg 23 · -47% w/w

a month agotoday

Installs / week

pypi · massive-context-mcp

Stars

0 open issues

19 Jan 2026

Last commit

from GitHub

MIT

License

Python

What the code does

We read the source, 4 d ago · rules 995398eba69f

A tool parameter reaches a dangerous call

A value the model can set ends up inside a file or shell call. That is not a flaw by itself — for a terminal server it is the job — but it is where things go wrong when it is not.

A tool parameter reaches a dangerous call rlm_setup_ollama.install → src/rlm_mcp_server.py:721, rlm_setup_ollama.model → src/rlm_mcp_server.py:792, rlm_setup_ollama_direct.model → src/rlm_mcp_server.py:658

                install_proc = subprocess.run(

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

A tool parameter here reaches a dangerous call

That is not a flaw by itself — but it is where things go wrong when it is not the job. We re-read this code on every release. Watch it and you hear from us the day another one appears.

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add massive-context-mcp -- uvx massive-context-mcp

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

{
  "mcpServers": {
    "massive-context-mcp": {
      "command": "uvx",
      "args": [
        "massive-context-mcp"
      ]
    }
  }
}

~/.codex/config.toml

[mcp_servers.massive-context-mcp]
command = "uvx"
args = ["massive-context-mcp"]

.cursor/mcp.json

{
  "mcpServers": {
    "massive-context-mcp": {
      "command": "uvx",
      "args": [
        "massive-context-mcp"
      ]
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "massive-context-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "massive-context-mcp"
      ]
    }
  }
}

Optional settings from the registry entry, left out of the block above: RLM_DATA_DIR (Directory for storing context data), OLLAMA_URL (URL for Ollama server (default: http://localhost:11434)).

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Massive Context MCP — questions

Answers built from our own checks of this server.

Why is there no uptime for Massive Context MCP?

Massive Context MCP runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package massive-context-mcp was installed 86 times last week.

How do I connect Massive Context MCP?

Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It runs locally, so the command pulls massive-context-mcp straight from pypi; nothing to host, nothing to sign up for.

How many people use Massive Context MCP?

The pypi package massive-context-mcp was installed 86 times in the last week. Week over week that is -47%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.

Is Massive Context MCP open source?

Yes — it is published under the MIT licence, written in Python and 1 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.