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Installation

github-actions[bot] edited this page May 18, 2026 · 6 revisions

Installation Guide

This guide covers all installation methods for NeuralMind, including system requirements, dependencies, and platform-specific instructions.

NeuralMind is a local, offline Python package — no SaaS, no accounts, no outbound calls. Once installed, it works from the CLI, via its MCP server, and (for Claude Code) as a PostToolUse compression layer. See the Setup Guide for post-install configuration or Use Cases to pick a workflow first.

Table of Contents


Install — pick your path

New in v0.7.0. NeuralMind installs five ways. All paths deliver the same package — the neuralmind CLI, the neuralmind-mcp server, and the Python module.

Method Command When to pick
pip pip install neuralmind graphifyy Default. Drops it in your active env.
pipx pipx install neuralmind && pipx inject neuralmind graphifyy Global CLI, no env pollution.
uv uv pip install neuralmind graphifyy Modern, fast Python tooling.
Docker docker pull ghcr.io/dfrostar/neuralmind:latest && docker run --rm -v "$PWD:/project:ro" ghcr.io/dfrostar/neuralmind:latest neuralmind --help Containerized — no Python on the host. Multi-platform (linux/amd64 + linux/arm64); auto-published to GHCR on every release since v0.9.0.
From source git clone https://github.com/dfrostar/neuralmind && pip install -e . Hacking on NeuralMind itself.

Verify any install:

neuralmind --help     # works for every path

# For pip / uv / source (a Python env where neuralmind is importable):
python -c "import neuralmind; print(neuralmind.__version__)"

Full walkthrough with pros and cons of each path: Install paths.

The sections below remain the deep reference — system requirements, dependency tables, platform-specific notes, and troubleshooting.


System Requirements

Minimum Requirements

Component Requirement
Python 3.10 or higher
Memory 2GB RAM (4GB+ recommended for large codebases)
Storage 500MB for base install + space for embeddings
OS Linux, macOS, Windows 10+

Software Prerequisites

  1. Python 3.10+: Download from python.org
  2. pip (or pipx / uv): Usually included with Python
  3. git (optional): For source installation
  4. graphify: For generating knowledge graphs from codebases (installed alongside NeuralMind in every path above)

Quick Install

For most users, the quickest path:

# Install NeuralMind
pip install neuralmind

# Install graphify for knowledge graph generation
pip install graphifyy

# Verify installation
neuralmind --help

Prefer one of the other four install paths? See the install matrix above.


Installation Methods

From PyPI

The default installation method.

Default Installation

pip install neuralmind

This includes everything most users need: the CLI, the semantic indexing layer, and the MCP server (neuralmind-mcp) for Claude Desktop, Claude Code, Cursor, Cline, Continue, Hermes-Agent, OpenClaw, and any other MCP-compatible client.

Note for users upgrading from v0.4.x or earlier: the MCP server used to be gated behind an [mcp] extra. From v0.5.0 onward it ships in the base package. Existing pip install "neuralmind[mcp]" commands still work — the mcp extra is preserved as an empty no-op for backwards compatibility.

With Development Tools

For contributors or those who want testing/linting tools:

pip install neuralmind[dev]

Full Installation

All extras (equivalent to [dev] since v0.5.0):

pip install neuralmind[all]

pipx

pipx installs each Python application in its own dedicated venv and exposes the entry points on your PATH globally. neuralmind and neuralmind-mcp are then available from any directory without activating anything.

pipx install neuralmind
pipx inject neuralmind graphifyy

Trade-off: because pipx isolates the package, import neuralmind from your project's own Python won't work. If you also script against the Python API, use pip in a project venv instead.

uv

uv is Astral's Rust-based Python package manager — significantly faster installs, drop-in for pip, compatible venvs.

uv pip install neuralmind graphifyy

For a uv-managed project:

uv add neuralmind graphifyy

Docker

Pull from GHCR (auto-published since v0.9.0, multi-platform linux/amd64 + linux/arm64):

docker pull ghcr.io/dfrostar/neuralmind:latest
# or pin a specific version
docker pull ghcr.io/dfrostar/neuralmind:v0.9.0

# Run the MCP server. `neuralmind-mcp` ignores any CLI args; each MCP
# tool call (neuralmind_wakeup, neuralmind_query, …) carries its own
# `project_path` argument that the client passes in. The mount below
# just exposes the project tree so those tool calls can find the path.
docker run --rm -i \
  -v "$PWD:/project:ro" \
  ghcr.io/dfrostar/neuralmind:latest neuralmind-mcp

# Run the graph view on http://localhost:8765
docker run --rm -p 8765:8765 \
  -v "$PWD:/project:ro" \
  ghcr.io/dfrostar/neuralmind:latest \
  neuralmind serve /project --host 0.0.0.0 --no-auth

Local build — if you want to build the image yourself from the repo's Dockerfile: docker build -t neuralmind:dev . then substitute neuralmind:dev for ghcr.io/dfrostar/neuralmind:latest in the commands above.

To persist the index between runs, mount the project directory read-write so .neuralmind/ and graphify-out/ land on the host:

docker run --rm -v "$PWD:/project" ghcr.io/dfrostar/neuralmind:latest neuralmind build /project

From Source

For the latest development version or contributors:

# Clone the repository
git clone https://github.com/dfrostar/neuralmind.git
cd neuralmind

# Install in editable mode
pip install -e .

# Or with dev tools
pip install -e ".[dev]"

Development Installation

Recommended setup for contributors:

# Clone and enter directory
git clone https://github.com/dfrostar/neuralmind.git
cd neuralmind

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Linux/macOS
# or: venv\Scripts\activate  # Windows

# Install with dev dependencies
pip install -e ".[dev]"

# Install pre-commit hooks (optional)
pre-commit install

Dependencies

Core Dependencies (Automatically Installed)

Package Version Purpose
chromadb ≥0.4.0 Vector database for embeddings
pyyaml ≥6.0 Configuration file parsing
toml ≥0.10 TOML configuration file support
mcp ≥1.23.0 Model Context Protocol server (since v0.5.0)

Optional Dependencies

Dev Extra (pip install neuralmind[dev])

Package Version Purpose
pytest ≥7.0 Testing framework
pytest-asyncio ≥0.21.0 Async test support
black ≥23.0 Code formatting
ruff ≥0.1.0 Fast linting

Legacy [mcp] extra

pip install "neuralmind[mcp]" still resolves cleanly — the extra is preserved as an empty no-op so existing install commands in user docs, blog posts, and CI configs keep working. No reason to use it in new commands; pip install neuralmind already includes the MCP server.

External Tools

Tool Installation Purpose
graphify pip install graphifyy Knowledge graph generation

Platform-Specific Instructions

Linux (Ubuntu/Debian)

# Ensure Python 3.10+ is installed
sudo apt update
sudo apt install python3.10 python3.10-venv python3-pip

# Create virtual environment (recommended)
python3.10 -m venv neuralmind-env
source neuralmind-env/bin/activate

# Install NeuralMind
pip install neuralmind

macOS

# Using Homebrew
brew install python@3.11

# Create virtual environment
python3.11 -m venv neuralmind-env
source neuralmind-env/bin/activate

# Install NeuralMind
pip install neuralmind

Windows

# Ensure Python 3.10+ is installed from python.org
# Open PowerShell as Administrator

# Create virtual environment
python -m venv neuralmind-env
.\neuralmind-env\Scripts\Activate.ps1

# Install NeuralMind
pip install neuralmind

Docker

Use the repo's Dockerfile — multi-stage, non-root, transitive deps pre-wheeled in the builder stage so the runtime image doesn't need a C toolchain. See the Docker section above for the build and run commands, or the install-paths walkthrough for persistence and security notes.

If you want a minimal app-style Dockerfile for embedding NeuralMind inside another image:

FROM python:3.12-slim

WORKDIR /app

# Install NeuralMind (MCP server is bundled by default) + graph builder
RUN pip install --no-cache-dir neuralmind graphifyy

# Your project files
COPY . .

CMD ["neuralmind-mcp"]

Verification

Check Installation

# Check CLI is available — works for every install path
neuralmind --help

# Check version — pip / uv / source paths only
# (pipx isolates the package in its own venv; Docker runs in-container)
python -c "import neuralmind; print(neuralmind.__version__)"

Verify Dependencies

# Check ChromaDB
python -c "import chromadb; print(f'ChromaDB version: {chromadb.__version__}')"

# Check graphify (if installed)
graphify --help

Test with Sample Project

# Create a test directory
mkdir test-neuralmind
cd test-neuralmind

# Create a simple Python file
echo 'def hello(): return "world"' > hello.py

# Generate knowledge graph (requires graphify)
graphify update .

# Build neural index
neuralmind build .

# Test query
neuralmind wakeup .

Troubleshooting

Common Issues

"Command not found: neuralmind"

Cause: Python scripts directory not in PATH.

Solution:

# Linux/macOS
export PATH="$HOME/.local/bin:$PATH"

# Then retry
neuralmind --help

"No module named 'chromadb'"

Cause: Dependencies not installed properly.

Solution:

pip install --upgrade neuralmind
# or
pip install chromadb>=0.4.0

"graph.json not found"

Cause: Knowledge graph not generated.

Solution:

# Install graphify if not present
pip install graphifyy

# Generate knowledge graph
graphify update /path/to/your/project

# Then build neural index
neuralmind build /path/to/your/project

Memory Error on Large Codebases

Cause: Insufficient RAM for embedding generation.

Solution:

  • Close other applications
  • Process in batches using --force flag to rebuild incrementally
  • Consider using a machine with more RAM

SSL Certificate Errors

Cause: Corporate proxy or certificate issues.

Solution:

pip install --trusted-host pypi.org --trusted-host pypi.python.org neuralmind

Getting Help


Next Steps

After installation:

  1. Generate a knowledge graph for your project
  2. Build the neural index using neuralmind build
  3. Query your codebase with natural language
  4. Set up MCP integration for Claude Desktop

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