Skip to main content

Extracts, adapts, and deploys battle-tested features from existing codebases to new projects—complete with all dependencies, configurations, and framework integrations.

Project description

SpeedBuild

PyPI version License: Apache Python 3.8+

SpeedBuild is a local tool that extracts reusable code features from your existing codebase and makes them available through an MCP server. This helps AI coding tools (like Cursor, Claude, or Copilot) reference past implementations when generating new code, leading to more consistent results.

It runs entirely on your machine, uses your own LLM API keys, and stores data locally in Chroma (for vectors) and SQLite.

Currently focused on Django and Express projects, with support for their common patterns.

How it works

  1. Initialize in your project:

    speedbuild init
    
  2. Extract and store reusable features from your code:

    speedbuild find
    
  3. Get the MCP configuration:

    speedbuild mcp-config
    

    Copy the output and paste it into your IDE or AI tool (e.g., Cursor or VS Code settings for MCP servers).

That's it. Now, when you ask your AI tool to implement something (e.g., "add user registration like we do it"), it can pull references from your extracted features, including dependencies.

You provide your own LLM API keys. You can configure different models/providers for tasks like:

  • Classification (finding features)
  • Documentation (generating docs)
  • Retrieval (natural language code search)

Everything runs locally—no data leaves your system.

Installation

pip install speedbuild

or check the releases on GitHub.

speedbuild config

to setup llm configuration and specify which models to use.

Future plans

Phase 2 will add:

  • Versioning of extracted features
  • Collaboration (sharing across team members)
  • Monitoring

These will be paid features.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

speedbuild-0.1.8.tar.gz (103.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

speedbuild-0.1.8-py3-none-any.whl (132.9 kB view details)

Uploaded Python 3

File details

Details for the file speedbuild-0.1.8.tar.gz.

File metadata

  • Download URL: speedbuild-0.1.8.tar.gz
  • Upload date:
  • Size: 103.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.3

File hashes

Hashes for speedbuild-0.1.8.tar.gz
Algorithm Hash digest
SHA256 6e969cdf20a62675e2118b7886322a58e07f36620f4051c516465241b58d042a
MD5 fd304955322001f044640ba6d08cf5d4
BLAKE2b-256 930c6409ef5469aa826e9a4d0c17ff49bbe3d095698292416d6e34df1397aa82

See more details on using hashes here.

File details

Details for the file speedbuild-0.1.8-py3-none-any.whl.

File metadata

  • Download URL: speedbuild-0.1.8-py3-none-any.whl
  • Upload date:
  • Size: 132.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.3

File hashes

Hashes for speedbuild-0.1.8-py3-none-any.whl
Algorithm Hash digest
SHA256 fd3294fdfdc31445a692c694edbe0fefec154773311ff264308c75312fa1399d
MD5 21b4510c37145e4785f3ea54f0d39f46
BLAKE2b-256 225384e7c7b9666a34eca9dbae9fca22d1bc08a1bc8433ac1cbd680e1da6699b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page